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diff --git a/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html b/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html
index 2b9f5ffba8dc6c97279d7eaa505046c32f5ad279..b2a554f9d1d699f93ce322d320ea14e1747b469e 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html
@@ -388,7 +388,7 @@
 <tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_bayes_factor" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_bayes_factor"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_bayes_factor</span></code></a>(BME_dict[, plot_name])</p></td>
 <td><p>Plots the Bayes factor distibutions in a <span class="math notranslate nohighlight">\(N_m \times N_m\)</span> matrix, where <span class="math notranslate nohighlight">\(N_m\)</span> is the number of the models.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_just_analysis</span></code></a>(model_weights_dict)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_just_analysis</span></code></a>()</p></td>
 <td><p>Visualizes the confusion matrix and the model wights for the justifiability analysis.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_model_weights" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_model_weights"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_model_weights</span></code></a>(model_weights, plot_name)</p></td>
@@ -559,7 +559,7 @@ matrix, where <span class="math notranslate nohighlight">\(N_m\)</span> is the n
 
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis">
-<span class="sig-name descname"><span class="pre">plot_just_analysis</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_weights_dict</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_just_analysis</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="Link to this definition">¶</a></dt>
 <dd><p>Visualizes the confusion matrix and the model wights for the
 justifiability analysis.</p>
 <section id="id13">
diff --git a/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html b/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html
index 1c766909b66ee0fbeee63c3605370175ed825f8a..582ffdbf17a4c5da276dcc5ee63023cb029f1b4e 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html
@@ -362,6 +362,32 @@ science, 5(1), pp.65-80.</p>
 <dl class="simple">
 <dt>BayesOpts<span class="classifier">obj</span></dt><dd><p>Bayes object.</p>
 </dd>
+<dt>engine<span class="classifier">bayesvalidrox.Engine</span></dt><dd><p>Engine object that contains the surrogate, model and expdesign</p>
+</dd>
+<dt>mcmc_params<span class="classifier">dict</span></dt><dd><p>Dictionary of parameters for the mcmc. Required are
+- init_samples
+- n_steps
+- n_walkers
+- n_burn
+- moves
+- multiplrocessing
+- verbose</p>
+</dd>
+<dt>Discrepancy<span class="classifier">bayesvalidrox.Discrepancy</span></dt><dd><p>Discrepancy object that described the uncertainty of the data.</p>
+</dd>
+</dl>
+<p>bias_inputs :</p>
+<p>error_model :</p>
+<p>req_outputs :</p>
+<p>selected_indices :</p>
+<p>emulator :</p>
+<dl class="simple">
+<dt>out_dir<span class="classifier">string</span></dt><dd><p>Directory to write the outputs to.</p>
+</dd>
+<dt>name<span class="classifier">string</span></dt><dd><p>Name of this MCMC selection (?)</p>
+</dd>
+<dt>BiasInputs<span class="classifier"></span></dt><dd><p>The default is None.</p>
+</dd>
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.bayes_inference.mcmc.MCMC.__init__">
diff --git a/docs/build/html/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html b/docs/build/html/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html
index 868fd803201d3bf3f5b07955c8755ebf4ecd837f..312c77782cd414fca80162767cf9ae9f76aa5b10 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html
@@ -339,7 +339,7 @@
 <h1>bayesvalidrox.pylink.pylink.PyLinkForwardModel<a class="headerlink" href="#bayesvalidrox-pylink-pylink-pylinkforwardmodel" title="Link to this heading">¶</a></h1>
 <dl class="py class">
 <dt class="sig sig-object py" id="bayesvalidrox.pylink.pylink.PyLinkForwardModel">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">bayesvalidrox.pylink.pylink.</span></span><span class="sig-name descname"><span class="pre">PyLinkForwardModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="Link to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">bayesvalidrox.pylink.pylink.</span></span><span class="sig-name descname"><span class="pre">PyLinkForwardModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">store</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out_dir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>A forward model binder</p>
 <p>This calss serves as a code wrapper. This wrapper allows the execution of
@@ -428,7 +428,7 @@ This is only available for one output.</p>
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.pylink.pylink.PyLinkForwardModel.__init__">
-<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel.__init__" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">store</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out_dir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel.__init__" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <p class="rubric">Methods</p>
diff --git a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html
index d9bc2a754cec48165661ad78b544fd137effc6c1..563940f5f58e78060a2aec37e0a98ba870af368f 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html
@@ -465,7 +465,7 @@ Run_No : int</p>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.engine.Engine.eval_metamodel">
-<span class="sig-name descname"><span class="pre">eval_metamodel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nsamples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sampling_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.engine.Engine.eval_metamodel" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">eval_metamodel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nsamples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sampling_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parallel</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.engine.Engine.eval_metamodel" title="Link to this definition">¶</a></dt>
 <dd><p>Evaluates metamodel at the requested samples. One can also generate
 nsamples.</p>
 <section id="id3">
@@ -481,6 +481,9 @@ default is None.</p>
 </dd>
 <dt>return_samples<span class="classifier">bool, optional</span></dt><dd><p>Retun samples, if no <cite>samples</cite> is provided. The default is False.</p>
 </dd>
+<dt>parallel<span class="classifier">bool, optional</span></dt><dd><p>Set to true if the evaluations should be done in parallel.
+The default is False.</p>
+</dd>
 </dl>
 </section>
 <section id="id4">
diff --git a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html
index 78f9787e11a1f9ebd7beac6d2f79d1f5dcc303b7..6548c9a3976e781288bcb9afb7f18c13f91d17bb 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html
@@ -560,12 +560,12 @@ the MetaModel object.</p>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.init_param_space">
-<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.init_param_space" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.init_param_space" title="Link to this definition">¶</a></dt>
 <dd><p>Initializes parameter space.</p>
 <section id="id6">
 <h3>Parameters<a class="headerlink" href="#id6" title="Link to this heading">¶</a></h3>
 <dl class="simple">
-<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>None</cite>.</p>
+<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>1</cite>.</p>
 </dd>
 </dl>
 </section>
diff --git a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html
index b5eb76fa2d343182c07caac085a2d114701e1ff4..84255758844702fe963c162951be225f2f713774 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html
@@ -417,12 +417,12 @@ the MetaModel object.</p>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.input_space.InputSpace.init_param_space">
-<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.input_space.InputSpace.init_param_space" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.input_space.InputSpace.init_param_space" title="Link to this definition">¶</a></dt>
 <dd><p>Initializes parameter space.</p>
 <section id="id2">
 <h3>Parameters<a class="headerlink" href="#id2" title="Link to this heading">¶</a></h3>
 <dl class="simple">
-<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>None</cite>.</p>
+<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>1</cite>.</p>
 </dd>
 </dl>
 </section>
diff --git a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html
index 49744e8097ad29d88b38c04284f137b188ee2946..07bf13ba0b8fa37029609e50352dc6c58416f484 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html
@@ -449,8 +449,8 @@ For experimental design refer to <cite>InputSpace</cite>.</p>
 <tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.generate_polynomials" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.generate_polynomials"><code class="xref py py-obj docutils literal notranslate"><span class="pre">generate_polynomials</span></code></a>([max_deg])</p></td>
 <td><p>Generates (univariate) polynomials.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pca_transformation</span></code></a>(target[, verbose])</p></td>
-<td><p>Transforms the targets (outputs) via Principal Component Analysis</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pca_transformation</span></code></a>(target)</p></td>
+<td><p>Transforms the targets (outputs) via Principal Component Analysis.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.regression" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.regression"><code class="xref py py-obj docutils literal notranslate"><span class="pre">regression</span></code></a>(X, y, basis_indices[, ...])</p></td>
 <td><p>Fit regression using the regression method provided.</p></td>
@@ -720,16 +720,15 @@ The default is False.</p>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation">
-<span class="sig-name descname"><span class="pre">pca_transformation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="Link to this definition">¶</a></dt>
-<dd><p>Transforms the targets (outputs) via Principal Component Analysis</p>
+<span class="sig-name descname"><span class="pre">pca_transformation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="Link to this definition">¶</a></dt>
+<dd><p>Transforms the targets (outputs) via Principal Component Analysis.
+The number of features is set by <cite>self.n_pca_components</cite>.
+If this is not given, <cite>self.var_pca_threshold</cite> is used as a threshold.</p>
 <section id="id14">
 <h3>Parameters<a class="headerlink" href="#id14" title="Link to this heading">¶</a></h3>
 <dl class="simple">
 <dt>target<span class="classifier">array of shape (n_samples,)</span></dt><dd><p>Target values.</p>
 </dd>
-<dt>verbose<span class="classifier">bool</span></dt><dd><p>Set to True to get more information during functtion call.
-The default is False.</p>
-</dd>
 </dl>
 </section>
 <section id="id15">
@@ -804,7 +803,7 @@ for the fast version of the bootstrapping.</p>
 <section id="id20">
 <h3>Parameters<a class="headerlink" href="#id20" title="Link to this heading">¶</a></h3>
 <dl class="simple">
-<dt>X<span class="classifier">array of shape (n_samples, n_params)</span></dt><dd><p>Training set.</p>
+<dt>X<span class="classifier">array of shape (n_samples, n_params)</span></dt><dd><p>Training set. These samples should be already transformed.</p>
 </dd>
 <dt>y<span class="classifier">array of shape (n_samples, n_outs)</span></dt><dd><p>The (transformed) model responses.</p>
 </dd>
diff --git a/docs/build/html/_sources/bayes_description.rst.txt b/docs/build/html/_sources/bayes_description.rst.txt
index 2cfd3a6a8c43868b09f404eafdd36594ed9c3c7d..0406162ed8a5927c2f3aa1944142584820c20d75 100644
--- a/docs/build/html/_sources/bayes_description.rst.txt
+++ b/docs/build/html/_sources/bayes_description.rst.txt
@@ -1,7 +1,62 @@
-Bayesian inference and multi-model comparison
-*********************************************
+Bayesian inference
+******************
+.. container:: twocol
 
+   .. container:: leftside
+   
+      With Bayesian inference we ask the question 'how does our understanding of the inputs change given some observation of the outputs of the model?', i.e. we perform an updating step of the prior distributions to posterior, based on some observations.
+      Bayesvalidrox provides a dedicated class to perform this task, :any:`bayesvalidrox.bayes_inference.bayes_inference.BayesInference`, which infers the posterior via ``rejection-sampling`` or ``MCMC``.
+      The likelihood in rejection sampling is estimated with the help of ``bootstrapping``.
+      MCMC-specific parameters are to be given as a dictionary called ``mcmc_params`` and can include 
+	  
+      * ``init_samples``: initial samples 
+      * ``n_steps``: number of steps 
+      * ``n_walkers``: number of walkers
+      * ``n_burn``: length of the burn-in 
+      * ``moves``: function to use for the moves, e.g. taken from ``emcee``
+      * ``multiprocessing``: setting for multiprocessing
+      * ``verbose``: verbosity 
+	  
+   .. container:: rightside
+   
+      .. image:: ../diagrams/bayesian_validation.png
+         :width: 300
+         :alt: UML diagram for classes related to Bayesian inference.
+
+The observation should be set as ``Model.observations`` in the ``Engine``, and an estimation of its uncertainty can be provided as a :any:`bayesvalidrox.bayes_inference.discrepancy.Discrepancy` object.
+
+Example
+=======
+For this example we need to add the following imports.
+
+>>> from bayesvalidrox import Discrepancy, BayesInference
+
+In order to run Bayesian inference we first need to provide an observation.
+For this example we take an evaluation of the model on some chosen sample and add the resulting values as ``Model.observations``.
+As this expects a 1D-array for each output key, we need to change the format slightly.
+
+>>> true_sample = [[2]]
+>>> observation = Model.run_model_parallel(true_sample)
+>>> Model.observations = {}
+>>> for key in observation:
+>>>     if key == 'x_values':
+>>>         Model.observations[key]=observation[key]
+>>>     else:
+>>>         Model.observations[key]=observation[key][0]
+
+Next we define the uncertainty on the observation with the class :any:`bayesvalidrox.bayes_inference.discrepancy.Discrepancy`.
+For this example we set the uncertainty to be zero-mean gaussian and dependent on the values in the observation, i.e. larger values have a larger uncertainty associated with them.
+The ``parameters`` contain the variance for each point in the observation.
+
+>>> obsData = pd.DataFrame(Model.observations, columns=Model.Output.names)
+>>> DiscrepancyOpts = Discrepancy('')
+>>> DiscrepancyOpts.type = 'Gaussian'
+>>> DiscrepancyOpts.parameters = obsData**2
+
+Now we can initialize an object of class :any:`bayesvalidrox.bayes_inference.bayes_inference.BayesInference` with all the wanted properties.
+This object has to be given our ``Engine``.
+If it should use the surrogate during inference, set ``emulator`` to ``True``, otherwise the model will be evaluated directly.
+
+>>> BayesObj = BayesInference(Engine_)
+>>> BayesObj.emulator = True
 
-.. image:: ../diagrams/bayesian_validation.png
-   :width: 300
-   :alt: UML diagram for classes related to Bayesian inference and multi-model comparison.
diff --git a/docs/build/html/_sources/bmc_description.rst.txt b/docs/build/html/_sources/bmc_description.rst.txt
new file mode 100644
index 0000000000000000000000000000000000000000..10e73bd1e819ad67df4fe48247a2bcf26fe698a7
--- /dev/null
+++ b/docs/build/html/_sources/bmc_description.rst.txt
@@ -0,0 +1,7 @@
+Bayesian multi-model comparison
+*******************************
+
+.. image:: ../diagrams/bayesian_model_comparison.png
+   :width: 400
+   :alt: UML diagram for classes related to Bayesian multi-model comparison.
+
diff --git a/docs/build/html/_sources/model_description.rst.txt b/docs/build/html/_sources/model_description.rst.txt
index bb719886b9a5a61cfed3f44eebcf810b5ca46ef8..923f20a7cb126bf4f068f6f824c6ba0c6f0f9f42 100644
--- a/docs/build/html/_sources/model_description.rst.txt
+++ b/docs/build/html/_sources/model_description.rst.txt
@@ -6,10 +6,10 @@ Models
    .. container:: leftside
    
       BayesValidRox gives options to create interfaces for a variety of models with the class :any:`bayesvalidrox.pylink.pylink.PyLinkForwardModel`.
-	  Its main function is to run the model on given samples and to read in and contain MC references and observations.
+      Its main function is to run the model on given samples and to read in and contain MC references and observations.
 	  
-	  Models can be defined via python functions, shell commands or as general executables.
-	  This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.
+      Models can be defined via python functions, shell commands or as general executables.
+      This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.
 
    .. container:: rightside
    
diff --git a/docs/build/html/_sources/packagedescription.rst.txt b/docs/build/html/_sources/packagedescription.rst.txt
index f245959b8d5a4b1d56de4e9cc86cff64b2da9b98..1d1fd65173851b1c5942f7da35568c2fd3e4c696 100644
--- a/docs/build/html/_sources/packagedescription.rst.txt
+++ b/docs/build/html/_sources/packagedescription.rst.txt
@@ -69,3 +69,4 @@ The next pages lead through the topics given in BayesValidRox and describe the a
    al_description
    post_description
    bayes_description
+   bmc_description
diff --git a/docs/build/html/_sources/post_description.rst.txt b/docs/build/html/_sources/post_description.rst.txt
index af2172709f4581abfabdcfd06257edfa808aa501..987f18e7dbf8ea21cc987265bbbac7ac7a8d2ee1 100644
--- a/docs/build/html/_sources/post_description.rst.txt
+++ b/docs/build/html/_sources/post_description.rst.txt
@@ -4,11 +4,11 @@ Postprocessing
 
    .. container:: leftside
    
-         Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
-         The BayesValidRox class :any:`bayesvalidrox.post_processing.post_processing.PostProcessing` includes functions that are applicable to all types of surrogate model.
+      Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
+      The BayesValidRox class :any:`bayesvalidrox.post_processing.post_processing.PostProcessing` includes functions that are applicable to all types of surrogate model.
 		 
-		 * ``valid_metamodel``: visualizing some metamodel runs against the corresponding model runs
-		 * ``check_accuracy``: computing the RMSE error of the surrogate model
+      * ``valid_metamodel``: visualizing some metamodel runs against the corresponding model runs
+      * ``check_accuracy``: computing the RMSE error of the surrogate model
 		 
    .. container:: rightside
 
diff --git a/docs/build/html/bayes_description.html b/docs/build/html/bayes_description.html
index 62bb18a5a39b10a142d3caf25cd09dea371f6d75..4d5cfd6c6778cb15ccdb15917a9df9b2c78f98ca 100644
--- a/docs/build/html/bayes_description.html
+++ b/docs/build/html/bayes_description.html
@@ -3,10 +3,10 @@
   <head><meta charset="utf-8"/>
     <meta name="viewport" content="width=device-width,initial-scale=1"/>
     <meta name="color-scheme" content="light dark"><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
-<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="TUTORIAL" href="tutorial.html" /><link rel="prev" title="Postprocessing" href="post_description.html" />
+<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="Bayesian multi-model comparison" href="bmc_description.html" /><link rel="prev" title="Postprocessing" href="post_description.html" />
 
     <!-- Generated with Sphinx 7.3.7 and Furo 2023.09.10 -->
-        <title>Bayesian inference and multi-model comparison - bayesvalidrox 1.0.0 documentation</title>
+        <title>Bayesian inference - bayesvalidrox 1.0.0 documentation</title>
       <link rel="stylesheet" type="text/css" href="_static/pygments.css?v=362ab14a" />
     <link rel="stylesheet" type="text/css" href="_static/styles/furo.css?v=135e06be" />
     <link rel="stylesheet" type="text/css" href="_static/styles/furo-extensions.css?v=36a5483c" />
@@ -141,7 +141,7 @@
           <svg class="theme-icon-when-light"><use href="#svg-sun"></use></svg>
         </button>
       </div>
-      <label class="toc-overlay-icon toc-header-icon no-toc" for="__toc">
+      <label class="toc-overlay-icon toc-header-icon" for="__toc">
         <div class="visually-hidden">Toggle table of contents sidebar</div>
         <i class="icon"><svg><use href="#svg-toc"></use></svg></i>
       </label>
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -329,15 +330,71 @@
               <svg class="theme-icon-when-light"><use href="#svg-sun"></use></svg>
             </button>
           </div>
-          <label class="toc-overlay-icon toc-content-icon no-toc" for="__toc">
+          <label class="toc-overlay-icon toc-content-icon" for="__toc">
             <div class="visually-hidden">Toggle table of contents sidebar</div>
             <i class="icon"><svg><use href="#svg-toc"></use></svg></i>
           </label>
         </div>
         <article role="main">
-          <section id="bayesian-inference-and-multi-model-comparison">
-<h1>Bayesian inference and multi-model comparison<a class="headerlink" href="#bayesian-inference-and-multi-model-comparison" title="Link to this heading">¶</a></h1>
-<a class="reference internal image-reference" href="_images/bayesian_validation.png"><img alt="UML diagram for classes related to Bayesian inference and multi-model comparison." src="_images/bayesian_validation.png" style="width: 300px;" /></a>
+          <section id="bayesian-inference">
+<h1>Bayesian inference<a class="headerlink" href="#bayesian-inference" title="Link to this heading">¶</a></h1>
+<div class="twocol docutils container">
+<div class="leftside docutils container">
+<p>With Bayesian inference we ask the question ‘how does our understanding of the inputs change given some observation of the outputs of the model?’, i.e. we perform an updating step of the prior distributions to posterior, based on some observations.
+Bayesvalidrox provides a dedicated class to perform this task, <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html#bayesvalidrox.bayes_inference.bayes_inference.BayesInference" title="bayesvalidrox.bayes_inference.bayes_inference.BayesInference"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.bayes_inference.BayesInference</span></code></a>, which infers the posterior via <code class="docutils literal notranslate"><span class="pre">rejection-sampling</span></code> or <code class="docutils literal notranslate"><span class="pre">MCMC</span></code>.
+The likelihood in rejection sampling is estimated with the help of <code class="docutils literal notranslate"><span class="pre">bootstrapping</span></code>.
+MCMC-specific parameters are to be given as a dictionary called <code class="docutils literal notranslate"><span class="pre">mcmc_params</span></code> and can include</p>
+<ul class="simple">
+<li><p><code class="docutils literal notranslate"><span class="pre">init_samples</span></code>: initial samples</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">n_steps</span></code>: number of steps</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">n_walkers</span></code>: number of walkers</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">n_burn</span></code>: length of the burn-in</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">moves</span></code>: function to use for the moves, e.g. taken from <code class="docutils literal notranslate"><span class="pre">emcee</span></code></p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">multiprocessing</span></code>: setting for multiprocessing</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">verbose</span></code>: verbosity</p></li>
+</ul>
+</div>
+<div class="rightside docutils container">
+<a class="reference internal image-reference" href="_images/bayesian_validation.png"><img alt="UML diagram for classes related to Bayesian inference." src="_images/bayesian_validation.png" style="width: 300px;" /></a>
+</div>
+</div>
+<p>The observation should be set as <code class="docutils literal notranslate"><span class="pre">Model.observations</span></code> in the <code class="docutils literal notranslate"><span class="pre">Engine</span></code>, and an estimation of its uncertainty can be provided as a <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html#bayesvalidrox.bayes_inference.discrepancy.Discrepancy" title="bayesvalidrox.bayes_inference.discrepancy.Discrepancy"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.discrepancy.Discrepancy</span></code></a> object.</p>
+<section id="example">
+<h2>Example<a class="headerlink" href="#example" title="Link to this heading">¶</a></h2>
+<p>For this example we need to add the following imports.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">bayesvalidrox</span> <span class="kn">import</span> <span class="n">Discrepancy</span><span class="p">,</span> <span class="n">BayesInference</span>
+</pre></div>
+</div>
+<p>In order to run Bayesian inference we first need to provide an observation.
+For this example we take an evaluation of the model on some chosen sample and add the resulting values as <code class="docutils literal notranslate"><span class="pre">Model.observations</span></code>.
+As this expects a 1D-array for each output key, we need to change the format slightly.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">true_sample</span> <span class="o">=</span> <span class="p">[[</span><span class="mi">2</span><span class="p">]]</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">observation</span> <span class="o">=</span> <span class="n">Model</span><span class="o">.</span><span class="n">run_model_parallel</span><span class="p">(</span><span class="n">true_sample</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">Model</span><span class="o">.</span><span class="n">observations</span> <span class="o">=</span> <span class="p">{}</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">observation</span><span class="p">:</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="k">if</span> <span class="n">key</span> <span class="o">==</span> <span class="s1">&#39;x_values&#39;</span><span class="p">:</span>
+<span class="gp">&gt;&gt;&gt; </span>        <span class="n">Model</span><span class="o">.</span><span class="n">observations</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">=</span><span class="n">observation</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="k">else</span><span class="p">:</span>
+<span class="gp">&gt;&gt;&gt; </span>        <span class="n">Model</span><span class="o">.</span><span class="n">observations</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">=</span><span class="n">observation</span><span class="p">[</span><span class="n">key</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
+</pre></div>
+</div>
+<p>Next we define the uncertainty on the observation with the class <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html#bayesvalidrox.bayes_inference.discrepancy.Discrepancy" title="bayesvalidrox.bayes_inference.discrepancy.Discrepancy"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.discrepancy.Discrepancy</span></code></a>.
+For this example we set the uncertainty to be zero-mean gaussian and dependent on the values in the observation, i.e. larger values have a larger uncertainty associated with them.
+The <code class="docutils literal notranslate"><span class="pre">parameters</span></code> contain the variance for each point in the observation.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">obsData</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">Model</span><span class="o">.</span><span class="n">observations</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="n">Model</span><span class="o">.</span><span class="n">Output</span><span class="o">.</span><span class="n">names</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">DiscrepancyOpts</span> <span class="o">=</span> <span class="n">Discrepancy</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">DiscrepancyOpts</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="s1">&#39;Gaussian&#39;</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">DiscrepancyOpts</span><span class="o">.</span><span class="n">parameters</span> <span class="o">=</span> <span class="n">obsData</span><span class="o">**</span><span class="mi">2</span>
+</pre></div>
+</div>
+<p>Now we can initialize an object of class <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html#bayesvalidrox.bayes_inference.bayes_inference.BayesInference" title="bayesvalidrox.bayes_inference.bayes_inference.BayesInference"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.bayes_inference.BayesInference</span></code></a> with all the wanted properties.
+This object has to be given our <code class="docutils literal notranslate"><span class="pre">Engine</span></code>.
+If it should use the surrogate during inference, set <code class="docutils literal notranslate"><span class="pre">emulator</span></code> to <code class="docutils literal notranslate"><span class="pre">True</span></code>, otherwise the model will be evaluated directly.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span> <span class="o">=</span> <span class="n">BayesInference</span><span class="p">(</span><span class="n">Engine_</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">emulator</span> <span class="o">=</span> <span class="kc">True</span>
+</pre></div>
+</div>
+</section>
 </section>
 
         </article>
@@ -345,12 +402,12 @@
       <footer>
         
         <div class="related-pages">
-          <a class="next-page" href="tutorial.html">
+          <a class="next-page" href="bmc_description.html">
               <div class="page-info">
                 <div class="context">
                   <span>Next</span>
                 </div>
-                <div class="title">TUTORIAL</div>
+                <div class="title">Bayesian multi-model comparison</div>
               </div>
               <svg class="furo-related-icon"><use href="#svg-arrow-right"></use></svg>
             </a>
@@ -383,9 +440,28 @@
         
       </footer>
     </div>
-    <aside class="toc-drawer no-toc">
+    <aside class="toc-drawer">
       
       
+      <div class="toc-sticky toc-scroll">
+        <div class="toc-title-container">
+          <span class="toc-title">
+            On this page
+          </span>
+        </div>
+        <div class="toc-tree-container">
+          <div class="toc-tree">
+            <ul>
+<li><a class="reference internal" href="#">Bayesian inference</a><ul>
+<li><a class="reference internal" href="#example">Example</a></li>
+</ul>
+</li>
+</ul>
+
+          </div>
+        </div>
+      </div>
+      
       
     </aside>
   </div>
diff --git a/docs/build/html/bmc_description.html b/docs/build/html/bmc_description.html
new file mode 100644
index 0000000000000000000000000000000000000000..03d4552b236f368fb27933296978b76f81b82ff7
--- /dev/null
+++ b/docs/build/html/bmc_description.html
@@ -0,0 +1,398 @@
+<!doctype html>
+<html class="no-js" lang="en" data-content_root="./">
+  <head><meta charset="utf-8"/>
+    <meta name="viewport" content="width=device-width,initial-scale=1"/>
+    <meta name="color-scheme" content="light dark"><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
+<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="TUTORIAL" href="tutorial.html" /><link rel="prev" title="Bayesian inference" href="bayes_description.html" />
+
+    <!-- Generated with Sphinx 7.3.7 and Furo 2023.09.10 -->
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+  
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+<li class="toctree-l4 has-children"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.html">bayesvalidrox.surrogate_models.orthogonal_matching_pursuit</a><input class="toctree-checkbox" id="toctree-checkbox-25" name="toctree-checkbox-25" role="switch" type="checkbox"/><label for="toctree-checkbox-25"><div class="visually-hidden">Toggle navigation of bayesvalidrox.surrogate_models.orthogonal_matching_pursuit</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr.html">bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit.html">bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit</a></li>
+</ul>
+</li>
+<li class="toctree-l4 has-children"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.html">bayesvalidrox.surrogate_models.reg_fast_ard</a><input class="toctree-checkbox" id="toctree-checkbox-26" name="toctree-checkbox-26" role="switch" type="checkbox"/><label for="toctree-checkbox-26"><div class="visually-hidden">Toggle navigation of bayesvalidrox.surrogate_models.reg_fast_ard</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions.html">bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD.html">bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD</a></li>
+</ul>
+</li>
+<li class="toctree-l4 has-children"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.html">bayesvalidrox.surrogate_models.reg_fast_laplace</a><input class="toctree-checkbox" id="toctree-checkbox-27" name="toctree-checkbox-27" role="switch" type="checkbox"/><label for="toctree-checkbox-27"><div class="visually-hidden">Toggle navigation of bayesvalidrox.surrogate_models.reg_fast_laplace</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace.html">bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace</a></li>
+</ul>
+</li>
+<li class="toctree-l4 has-children"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.html">bayesvalidrox.surrogate_models.surrogate_models</a><input class="toctree-checkbox" id="toctree-checkbox-28" name="toctree-checkbox-28" role="switch" type="checkbox"/><label for="toctree-checkbox-28"><div class="visually-hidden">Toggle navigation of bayesvalidrox.surrogate_models.surrogate_models</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error.html">bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.create_psi.html">bayesvalidrox.surrogate_models.surrogate_models.create_psi</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator.html">bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html">bayesvalidrox.surrogate_models.surrogate_models.MetaModel</a></li>
+</ul>
+</li>
+</ul>
+</li>
+</ul>
+</li>
+</ul>
+</li>
+</ul>
+
+</div>
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+      
+    </div>
+  </aside>
+  <div class="main">
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+        <article role="main">
+          <section id="bayesian-multi-model-comparison">
+<h1>Bayesian multi-model comparison<a class="headerlink" href="#bayesian-multi-model-comparison" title="Link to this heading">¶</a></h1>
+<a class="reference internal image-reference" href="_images/bayesian_model_comparison.png"><img alt="UML diagram for classes related to Bayesian multi-model comparison." src="_images/bayesian_model_comparison.png" style="width: 400px;" /></a>
+</section>
+
+        </article>
+      </div>
+      <footer>
+        
+        <div class="related-pages">
+          <a class="next-page" href="tutorial.html">
+              <div class="page-info">
+                <div class="context">
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+                <div class="title">TUTORIAL</div>
+              </div>
+              <svg class="furo-related-icon"><use href="#svg-arrow-right"></use></svg>
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+          <a class="prev-page" href="bayes_description.html">
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+          <div class="left-details">
+            <div class="copyright">
+                Copyright &#169; 2023, Farid Mohammadi, Rebecca Kohlhaas
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+</html>
\ No newline at end of file
diff --git a/docs/build/html/genindex.html b/docs/build/html/genindex.html
index 2b0791a3b4af33fa58bd71d15659bc6600d809eb..67a702598c7ef269e4c7bd789daf188a8d2611a0 100644
--- a/docs/build/html/genindex.html
+++ b/docs/build/html/genindex.html
@@ -168,7 +168,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/docs/build/html/index.html b/docs/build/html/index.html
index 460cf3cb78de9b9cd652a03cf2a89b74f44b34af..dcad29fd053e5f804ccff50405434996036a710f 100644
--- a/docs/build/html/index.html
+++ b/docs/build/html/index.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/docs/build/html/input_description.html b/docs/build/html/input_description.html
index 39e16d2b9c9ebbb21b05daa969ec7defe54b2f01..15276ff89db8a4735a131a0ee6fd8defc947bba0 100644
--- a/docs/build/html/input_description.html
+++ b/docs/build/html/input_description.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/docs/build/html/model_description.html b/docs/build/html/model_description.html
index 2dbaeed956d41cede70ba75d52434aab60a16698..da41e466709a96f632cca9cccb79f6e51e129f7f 100644
--- a/docs/build/html/model_description.html
+++ b/docs/build/html/model_description.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -339,12 +340,10 @@
 <h1>Models<a class="headerlink" href="#models" title="Link to this heading">¶</a></h1>
 <div class="twocol docutils container">
 <div class="leftside docutils container">
-<dl>
-<dt>BayesValidRox gives options to create interfaces for a variety of models with the class <a class="reference internal" href="_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="bayesvalidrox.pylink.pylink.PyLinkForwardModel"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.pylink.pylink.PyLinkForwardModel</span></code></a>.</dt><dd><p>Its main function is to run the model on given samples and to read in and contain MC references and observations.</p>
+<p>BayesValidRox gives options to create interfaces for a variety of models with the class <a class="reference internal" href="_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="bayesvalidrox.pylink.pylink.PyLinkForwardModel"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.pylink.pylink.PyLinkForwardModel</span></code></a>.
+Its main function is to run the model on given samples and to read in and contain MC references and observations.</p>
 <p>Models can be defined via python functions, shell commands or as general executables.
 This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.</p>
-</dd>
-</dl>
 </div>
 <div class="rightside docutils container">
 <a class="reference internal image-reference" href="_images/model.png"><img alt="UML diagram for the bayesvalidrox class :any:`bayesvalidrox.pylink.pylink.PyLinkForwardModel`." src="_images/model.png" style="width: 150px;" /></a>
diff --git a/docs/build/html/objects.inv b/docs/build/html/objects.inv
index b24151365f5b50ce51d7b5ed10cfdff340f22cf1..9269935a85e887aac2b1b3f13b91a4a9385002b6 100644
Binary files a/docs/build/html/objects.inv and b/docs/build/html/objects.inv differ
diff --git a/docs/build/html/packagedescription.html b/docs/build/html/packagedescription.html
index c76923ed2587b0b106908c8890e2adb48ed50353..875119c2724b77d8943b9bd3cb9f76be9c293d0e 100644
--- a/docs/build/html/packagedescription.html
+++ b/docs/build/html/packagedescription.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -382,7 +383,8 @@ If multiple (surrogate) models are given, they can be compared against each othe
 <li class="toctree-l1"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l1"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l1"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l1"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l1"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l1"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </div>
 </section>
diff --git a/docs/build/html/post_description.html b/docs/build/html/post_description.html
index d5eb2c29ef5a75b1b970f1b6d38b047b0d36cb55..33fa48a7a24fbaac8fc4bbd44531c37642a64171 100644
--- a/docs/build/html/post_description.html
+++ b/docs/build/html/post_description.html
@@ -3,7 +3,7 @@
   <head><meta charset="utf-8"/>
     <meta name="viewport" content="width=device-width,initial-scale=1"/>
     <meta name="color-scheme" content="light dark"><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
-<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="Bayesian inference and multi-model comparison" href="bayes_description.html" /><link rel="prev" title="Active learning: iteratively expanding the training set" href="al_description.html" />
+<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="Bayesian inference" href="bayes_description.html" /><link rel="prev" title="Active learning: iteratively expanding the training set" href="al_description.html" />
 
     <!-- Generated with Sphinx 7.3.7 and Furo 2023.09.10 -->
         <title>Postprocessing - bayesvalidrox 1.0.0 documentation</title>
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -341,12 +342,10 @@
 <div class="leftside docutils container">
 <p>Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
 The BayesValidRox class <a class="reference internal" href="_autosummary/bayesvalidrox.post_processing.post_processing.PostProcessing.html#bayesvalidrox.post_processing.post_processing.PostProcessing" title="bayesvalidrox.post_processing.post_processing.PostProcessing"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.post_processing.post_processing.PostProcessing</span></code></a> includes functions that are applicable to all types of surrogate model.</p>
-<blockquote>
-<div><ul class="simple">
+<ul class="simple">
 <li><p><code class="docutils literal notranslate"><span class="pre">valid_metamodel</span></code>: visualizing some metamodel runs against the corresponding model runs</p></li>
 <li><p><code class="docutils literal notranslate"><span class="pre">check_accuracy</span></code>: computing the RMSE error of the surrogate model</p></li>
 </ul>
-</div></blockquote>
 </div>
 <div class="rightside docutils container">
 <a class="reference internal image-reference" href="_images/postprocessing.png"><img alt="UML diagram for the classes and functions used in active learning in BayesValidRox." src="_images/postprocessing.png" style="width: 300px;" /></a>
@@ -407,7 +406,7 @@ The BayesValidRox class <a class="reference internal" href="_autosummary/bayesva
                 <div class="context">
                   <span>Next</span>
                 </div>
-                <div class="title">Bayesian inference and multi-model comparison</div>
+                <div class="title">Bayesian inference</div>
               </div>
               <svg class="furo-related-icon"><use href="#svg-arrow-right"></use></svg>
             </a>
diff --git a/docs/build/html/py-modindex.html b/docs/build/html/py-modindex.html
index a10614c9b79526a3d472e0d16dc897c071d4208e..9246a7ee0e6c25f120eaa3824bf53a47106fd299 100644
--- a/docs/build/html/py-modindex.html
+++ b/docs/build/html/py-modindex.html
@@ -168,7 +168,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/docs/build/html/search.html b/docs/build/html/search.html
index 8fe37498ef5854389bf8baad867f2b6e492744ad..5e4d1ba200ec4a1600843d12c68bcc37c194c2f4 100644
--- a/docs/build/html/search.html
+++ b/docs/build/html/search.html
@@ -167,7 +167,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/docs/build/html/searchindex.js b/docs/build/html/searchindex.js
index 3aaa01c41f479cebaf4856492681920308cc6705..fec129dec57603707f017d18b9b872cf33c52b35 100644
--- a/docs/build/html/searchindex.js
+++ b/docs/build/html/searchindex.js
@@ -1 +1 @@
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\ No newline at end of file
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"update_precis": 56, "user": 78, "valid": 72, "vblinearregress": 26, "within_rang": 17}})
\ No newline at end of file
diff --git a/docs/diagrams/bayesian_model_comparison.dot b/docs/diagrams/bayesian_model_comparison.dot
new file mode 100644
index 0000000000000000000000000000000000000000..7ed29281a18f49a9b81bff8d06e62bf9c9bb1b05
--- /dev/null
+++ b/docs/diagrams/bayesian_model_comparison.dot
@@ -0,0 +1,18 @@
+digraph pyUML {
+ExpDesigns [label="{ExpDesigns||}", shape=record];
+PyLinkForwardModel [label="{PyLinkForwardModel||}", shape=record];
+MetaModel [label="{MetaModel||}", shape=record];
+Engine [label="{Engine||}", shape=record];
+Engine -> PyLinkForwardModel  [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+Engine -> ExpDesigns  [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+Engine -> MetaModel  [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+Discrepancy [label="{Discrepancy||}", shape=record];
+BayesInference [label="{BayesInference||}", shape=record];
+BayesInference -> Engine  [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+BayesInference -> Discrepancy  [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+MCMC [label="{MCMC||}", shape=record];
+BayesInference -> MCMC  [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+MCMC -> Discrepancy  [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+BayesianModelComparison [label="{BayesianModelComparison|+ justifiability : bool\l+ perturbed_data : array\l+ n_bootstrap : int\l+ data_noise_level : float\l+ use_Bayes_settings : bool\l+ emulator : bool\l+ out_dir : string\l|+ setup()\l+ model_comparison_all()\l+ calc_bayes_factors\l+ calc_model_weights()\l+ calc_justifiability_analysis()\l+ generate_dataset()\l+ perturb_data()\l+ cal_model_weight()\l+ plot_just_analysis()\l+ plot_model_weights()\l+ plot_bayes_factor()\l}", shape=record];
+BayesianModelComparison -> BayesInference  [arrowtail=diamond, dir=back, headlabel="\n1..*", taillabel="\n1"];
+}
diff --git a/docs/diagrams/bayesian_validation.dot b/docs/diagrams/bayesian_validation.dot
index 46814289b17c73adefd12d435b34168a20c8dd24..1e66b0c1ae813b3c9adbf101c6f9d761bab8f433 100644
--- a/docs/diagrams/bayesian_validation.dot
+++ b/docs/diagrams/bayesian_validation.dot
@@ -10,4 +10,7 @@ Discrepancy [label="{Discrepancy||}", shape=record];
 BayesInference [label="{BayesInference|+ engine : Engine\l+ discrepancy : Discrepancy\l+ emulator : bool\l+ name : string\l+ bootatrap : bool\l+ req_outputs : list\l+ selected_indices : list\l+ prior_samples : array\l+ n_prior_samples : int\l+ measured_data : dict\l+ inference_method : string\l+ mcmc_params : dict\l+ bayes_loocv : bool\l+ n_bootstrap_itrs : int\l+ perturbed_data : lsit\l+ bootstrap_noise : double\l+ just_analysis : bool\l+ valid_metrics : list\l+ plot_post_pred : bool\l+ plot_map_pred : bool\l+ max_a_posteriori : string\l+ corner_title_fmt : string\l+ out_dir : string\l+ bmc : bool\l|+ setup_inference()\l+ create_inference()\l+ create_error_model()\l+ perform_bootstrap()\l+ _perturb_data()\l+ _eval_model()\l+ normpdf()\l+ _coor_Factor_BME()\l+ _rejection_sampling()\l+ _posterior_predictive()\l+ _plot_max_a_posteriori()\l+ plot_post_params()\l+ plot_log_BME()\l+ _plot_post_predictive()\l}", shape=record];
 BayesInference -> Engine  [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
 BayesInference -> Discrepancy  [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+MCMC [label="{MCMC|+ engine : Engine\l+ mcmc_params : dict\l+ Discrepancy : Discrepancy\l+ bias_inputs : dict\l+ error_model : MetaModel\l+ req_outputs : list\l+ selected_indices : array\l+ emulator : bool\l+ out_dir : string\l+ name : string\l|+ run_sampler()\l+ log_prior()\l+ log_likelihood()\l+ log_posterior()\l+ eval_model()\l+ train_error_model()\l+ normpdf()\l}", shape=record];
+BayesInference -> MCMC  [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+MCMC -> Discrepancy  [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
 }
diff --git a/docs/diagrams/class_diagram.py b/docs/diagrams/class_diagram.py
index 71567b36193c312d2f627a4f3a3ca04e04bfb350..3c9e17b1854273b1b5161996537fe1a5e9d2b44a 100644
--- a/docs/diagrams/class_diagram.py
+++ b/docs/diagrams/class_diagram.py
@@ -672,7 +672,6 @@ def generate_al_uml():
     
     print_and_save(graph, 'active_learning')
     
-       
 def generate_al_uml_reduced():
     """
     Generates the uml for active learning
@@ -868,11 +867,87 @@ def generate_bayes_uml():
     graph.add_composition(engine, bayesinf, multiplicity_parent = 1, multiplicity_child = 1)
     graph.add_composition(disc, bayesinf, multiplicity_parent = 1, multiplicity_child = 1)
     
+    # MCMC class 
+    mcmc = UMLClass('MCMC', 
+                    attributes = {
+                        'engine':'Engine', 
+                        'mcmc_params':'dict', 
+                        'Discrepancy':'Discrepancy', 
+                        'bias_inputs':'dict', 
+                        'error_model':'MetaModel', 
+                        'req_outputs':'list', 
+                        'selected_indices':'array', 
+                        'emulator':'bool',
+                        'out_dir':'string', 
+                        'name':'string',
+                        },
+                    methods = [
+                        'run_sampler()', 'log_prior()', 'log_likelihood()',
+                        'log_posterior()', 'eval_model()', 'train_error_model()',
+                        'normpdf()'
+                        ]
+                    )
+    graph.add_class(mcmc)
+    graph.add_composition(mcmc, bayesinf, multiplicity_parent=1, multiplicity_child=1)
+    graph.add_composition(disc, mcmc, multiplicity_parent=1, multiplicity_child=1)
+    
     print_and_save(graph, 'bayesian_validation')
                         
+
+def generate_bmc_uml():
+    graph = Graph('pyUML')
+    
+    expdesign = UMLClass('ExpDesigns')
+    graph.add_class(expdesign)
+    
+    model = UMLClass('PyLinkForwardModel')
+    graph.add_class(model)
+    
+    metamod = UMLClass('MetaModel')
+    graph.add_class(metamod)
+    
+    engine = UMLClass('Engine')
+    graph.add_class(engine)
+    graph.add_composition(model, engine, multiplicity_parent = 1, multiplicity_child = 1)
+    graph.add_composition(expdesign, engine, multiplicity_parent = 1, multiplicity_child = 1)
+    graph.add_composition(metamod, engine, multiplicity_parent = 1, multiplicity_child = 1)
     
-     
+    disc = UMLClass('Discrepancy')
+    graph.add_class(disc)
+    
+    bayesinf = UMLClass('BayesInference')
+    graph.add_class(bayesinf)
+    graph.add_composition(engine, bayesinf, multiplicity_parent = 1, multiplicity_child = 1)
+    graph.add_composition(disc, bayesinf, multiplicity_parent = 1, multiplicity_child = 1)
     
+    # MCMC class 
+    mcmc = UMLClass('MCMC')
+    graph.add_class(mcmc)
+    graph.add_composition(mcmc, bayesinf, multiplicity_parent=1, multiplicity_child=1)
+    graph.add_composition(disc, mcmc, multiplicity_parent=1, multiplicity_child=1)
+    
+    
+    # BMC
+    bmc = UMLClass('BayesianModelComparison',
+                   attributes = {'justifiability':'bool', 
+                                 'perturbed_data':'array',
+                                 'n_bootstrap':'int', 
+                                 'data_noise_level':'float',
+                                 'use_Bayes_settings':'bool', 
+                                 'emulator':'bool', 
+                                 'out_dir':'string'
+                                 },
+                   methods = ['setup()', 'model_comparison_all()','calc_bayes_factors',
+                              'calc_model_weights()', 'calc_justifiability_analysis()',
+                              'generate_dataset()', 'perturb_data()','cal_model_weight()',
+                              'plot_just_analysis()','plot_model_weights()', 'plot_bayes_factor()']
+                   )
+    graph.add_class(bmc)
+    graph.add_composition(bayesinf, bmc, multiplicity_parent=1, multiplicity_child='1..*')
+    
+    print_and_save(graph, 'bayesian_model_comparison')
+                        
+
 if __name__ == '__main__':
     
     generate_input_uml()
@@ -883,4 +958,5 @@ if __name__ == '__main__':
     generate_al_uml()
     generate_al_uml_reduced()
     generate_postprocessing_uml()
-    generate_bayes_uml()
\ No newline at end of file
+    generate_bayes_uml()
+    generate_bmc_uml()
\ No newline at end of file
diff --git a/docs/source/bayes_description.rst b/docs/source/bayes_description.rst
index 2cfd3a6a8c43868b09f404eafdd36594ed9c3c7d..1c72a3e9987ca89da79132dece7ba4626a218e96 100644
--- a/docs/source/bayes_description.rst
+++ b/docs/source/bayes_description.rst
@@ -1,7 +1,90 @@
-Bayesian inference and multi-model comparison
-*********************************************
+Bayesian inference
+******************
+.. container:: twocol
 
+   .. container:: leftside
+   
+      With Bayesian inference we ask the question 'how does our understanding of the inputs change given some observation of the outputs of the model?', i.e. we perform an updating step of the prior distributions to posterior, based on some observations.
+      Bayesvalidrox provides a dedicated class to perform this task, :any:`bayesvalidrox.bayes_inference.bayes_inference.BayesInference`, which infers the posterior via ``rejection-sampling`` or ``MCMC``.
+      The likelihood in rejection sampling is estimated with the help of ``bootstrapping``.
+      MCMC-specific parameters are to be given as a dictionary called ``mcmc_params`` and can include 
+	  
+      * ``init_samples``: initial samples 
+      * ``n_steps``: number of steps 
+      * ``n_walkers``: number of walkers
+      * ``n_burn``: length of the burn-in 
+      * ``moves``: function to use for the moves, e.g. taken from ``emcee``
+      * ``multiprocessing``: setting for multiprocessing
+      * ``verbose``: verbosity 
+	  
+   .. container:: rightside
+   
+      .. image:: ../diagrams/bayesian_validation.png
+         :width: 300
+         :alt: UML diagram for classes related to Bayesian inference.
 
-.. image:: ../diagrams/bayesian_validation.png
-   :width: 300
-   :alt: UML diagram for classes related to Bayesian inference and multi-model comparison.
+The observation should be set as ``Model.observations`` in the ``Engine``, and an estimation of its uncertainty can be provided as a :any:`bayesvalidrox.bayes_inference.discrepancy.Discrepancy` object.
+
+Example
+=======
+For this example we need to add the following imports.
+
+>>> from bayesvalidrox import Discrepancy, BayesInference
+
+In order to run Bayesian inference we first need to provide an observation.
+For this example we take an evaluation of the model on some chosen sample and add the resulting values as ``Model.observations``.
+As this expects a 1D-array for each output key, we need to change the format slightly.
+
+>>> true_sample = [[2]]
+>>> observation = Model.run_model_parallel(true_sample)
+>>> Model.observations = {}
+>>> for key in observation:
+>>>     if key == 'x_values':
+>>>         Model.observations[key]=observation[key]
+>>>     else:
+>>>         Model.observations[key]=observation[key][0]
+
+Next we define the uncertainty on the observation with the class :any:`bayesvalidrox.bayes_inference.discrepancy.Discrepancy`.
+For this example we set the uncertainty to be zero-mean gaussian and dependent on the values in the observation, i.e. larger values have a larger uncertainty associated with them.
+The ``parameters`` contain the variance for each point in the observation.
+
+>>> obsData = pd.DataFrame(Model.observations, columns=Model.Output.names)
+>>> DiscrepancyOpts = Discrepancy('')
+>>> DiscrepancyOpts.type = 'Gaussian'
+>>> DiscrepancyOpts.parameters = obsData**2
+
+Now we can initialize an object of class :any:`bayesvalidrox.bayes_inference.bayes_inference.BayesInference` with all the wanted properties.
+This object has to be given our ``Engine``.
+If it should use the surrogate during inference, set ``emulator`` to ``True``, otherwise the model will be evaluated directly.
+We also set the defined ``Discrepancy``. and set ``post_plot_pred`` if posterior predictions should be visualized.
+
+>>> BayesObj = BayesInference(Engine_)
+>>> BayesObj.emulator = True
+>>> BayesObj.Discrepancy = DiscrepancyOpts
+>>> BayesObj.plot_post_pred = True
+
+In order to run with rejection sampling, we set the ``inference_method`` accordingly and add properties for ``bootstrap``.
+
+>>> BayesObj.inference_method = 'rejection'
+>>> BayesObj.bootstrap = True
+>>> BayesObj.n_bootstrap_itrs = 500
+>>> BayesObj.bootstrap_noise = 2
+
+If the sampling should be done with MCMC, then this is set as the ``inference_method`` and additional properties are given in ``mcmc_params``.
+For this example we use the python package ``emcee`` to define the MCMC moves.
+
+>>> BayesObj.inference_method = 'MCMC'
+>>> import emcee
+>>> BayesObj.mcmc_params = {
+>>>     'n_steps': 1e4,#5,
+>>>     'n_walkers': 30,
+>>>     'moves': emcee.moves.KDEMove(),
+>>>     'multiprocessing': False,
+>>>     'verbose': False
+>>>     }
+
+Then we run the inference.
+
+>>> BayesObj.create_inference()
+
+If the output directory ``BayesObj.out_dir`` is not set otherwise, the outputs are written into the folder ``
\ No newline at end of file
diff --git a/docs/source/bmc_description.rst b/docs/source/bmc_description.rst
new file mode 100644
index 0000000000000000000000000000000000000000..10e73bd1e819ad67df4fe48247a2bcf26fe698a7
--- /dev/null
+++ b/docs/source/bmc_description.rst
@@ -0,0 +1,7 @@
+Bayesian multi-model comparison
+*******************************
+
+.. image:: ../diagrams/bayesian_model_comparison.png
+   :width: 400
+   :alt: UML diagram for classes related to Bayesian multi-model comparison.
+
diff --git a/docs/source/model_description.rst b/docs/source/model_description.rst
index bb719886b9a5a61cfed3f44eebcf810b5ca46ef8..923f20a7cb126bf4f068f6f824c6ba0c6f0f9f42 100644
--- a/docs/source/model_description.rst
+++ b/docs/source/model_description.rst
@@ -6,10 +6,10 @@ Models
    .. container:: leftside
    
       BayesValidRox gives options to create interfaces for a variety of models with the class :any:`bayesvalidrox.pylink.pylink.PyLinkForwardModel`.
-	  Its main function is to run the model on given samples and to read in and contain MC references and observations.
+      Its main function is to run the model on given samples and to read in and contain MC references and observations.
 	  
-	  Models can be defined via python functions, shell commands or as general executables.
-	  This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.
+      Models can be defined via python functions, shell commands or as general executables.
+      This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.
 
    .. container:: rightside
    
diff --git a/docs/source/packagedescription.rst b/docs/source/packagedescription.rst
index f245959b8d5a4b1d56de4e9cc86cff64b2da9b98..1d1fd65173851b1c5942f7da35568c2fd3e4c696 100644
--- a/docs/source/packagedescription.rst
+++ b/docs/source/packagedescription.rst
@@ -69,3 +69,4 @@ The next pages lead through the topics given in BayesValidRox and describe the a
    al_description
    post_description
    bayes_description
+   bmc_description
diff --git a/docs/source/post_description.rst b/docs/source/post_description.rst
index af2172709f4581abfabdcfd06257edfa808aa501..987f18e7dbf8ea21cc987265bbbac7ac7a8d2ee1 100644
--- a/docs/source/post_description.rst
+++ b/docs/source/post_description.rst
@@ -4,11 +4,11 @@ Postprocessing
 
    .. container:: leftside
    
-         Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
-         The BayesValidRox class :any:`bayesvalidrox.post_processing.post_processing.PostProcessing` includes functions that are applicable to all types of surrogate model.
+      Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
+      The BayesValidRox class :any:`bayesvalidrox.post_processing.post_processing.PostProcessing` includes functions that are applicable to all types of surrogate model.
 		 
-		 * ``valid_metamodel``: visualizing some metamodel runs against the corresponding model runs
-		 * ``check_accuracy``: computing the RMSE error of the surrogate model
+      * ``valid_metamodel``: visualizing some metamodel runs against the corresponding model runs
+      * ``check_accuracy``: computing the RMSE error of the surrogate model
 		 
    .. container:: rightside
 
diff --git a/examples/user_guide/example_user_guide.py b/examples/user_guide/example_user_guide.py
index f118d05a6fb03a1268de0fdfea56b963ce3514a5..3be56216f53be165b7284e1ef766380c5d3a2677 100644
--- a/examples/user_guide/example_user_guide.py
+++ b/examples/user_guide/example_user_guide.py
@@ -21,6 +21,9 @@ from bayesvalidrox.surrogate_models.surrogate_models import MetaModel
 from bayesvalidrox.surrogate_models.engine import Engine
 from bayesvalidrox.post_processing.post_processing import PostProcessing
 
+from bayesvalidrox.bayes_inference.bayes_inference import BayesInference
+from bayesvalidrox.bayes_inference.discrepancy import Discrepancy
+
 if __name__ == '__main__':
     #### Priors, input space and experimental design
     version = 1
@@ -100,4 +103,44 @@ if __name__ == '__main__':
     PostProc.check_accuracy(n_samples=10)
     PostProc.plot_moments()
     PostProc.sobol_indices()
-    PostProc.plot_seq_design_diagnostics()
\ No newline at end of file
+    PostProc.plot_seq_design_diagnostics()
+    
+    #### Bayesian inference
+    true_sample = [[2]]
+    observation, sample = Model.run_model_parallel(true_sample)
+    Model.observations = {}
+    for key in observation:
+        if key == 'x_values':
+            Model.observations[key]=observation[key]
+        else:
+            Model.observations[key]=observation[key][0]
+    
+    
+    obsData = pd.DataFrame(Model.observations, columns=Model.Output.names)
+    DiscrepancyOpts = Discrepancy('')
+    DiscrepancyOpts.type = 'Gaussian'
+    DiscrepancyOpts.parameters = obsData**2
+
+ 
+    BayesObj = BayesInference(Engine_)
+    BayesObj.emulator = True
+    BayesObj.Discrepancy = DiscrepancyOpts
+    BayesObj.plot_post_pred = True
+
+    BayesObj.bootstrap = True
+    BayesObj.n_bootstrap_itrs = 500
+    
+    BayesObj.inference_method = 'MCMC'#"MCMC"
+    import emcee
+    BayesObj.mcmc_params = {
+        'n_steps': 1e4,
+        'n_walkers': 30,
+        'moves': emcee.moves.KDEMove(),
+        'multiprocessing': False,
+        'verbose': False
+        }
+
+    BayesObj.create_inference()
+
+
+    
\ No newline at end of file
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diff --git a/public/.doctrees/tutorial.doctree b/public/.doctrees/tutorial.doctree
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diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html
index a8fbf99526166e7a511815115a03b9f56209f850..d6ae664d3a234e92f0775a6cb50dab94113152e6 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.html b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.html
index d5f4bdc76f24d30fb6c49cd17b346870ba53c969..be2a80de6a8e7f00e136d7bcf354bd2e691c833a 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html
index 2b9f5ffba8dc6c97279d7eaa505046c32f5ad279..8c36c6beaa669b19afc29e45796a9315b7896101 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -388,7 +389,7 @@
 <tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_bayes_factor" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_bayes_factor"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_bayes_factor</span></code></a>(BME_dict[, plot_name])</p></td>
 <td><p>Plots the Bayes factor distibutions in a <span class="math notranslate nohighlight">\(N_m \times N_m\)</span> matrix, where <span class="math notranslate nohighlight">\(N_m\)</span> is the number of the models.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_just_analysis</span></code></a>(model_weights_dict)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_just_analysis</span></code></a>()</p></td>
 <td><p>Visualizes the confusion matrix and the model wights for the justifiability analysis.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_model_weights" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_model_weights"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_model_weights</span></code></a>(model_weights, plot_name)</p></td>
@@ -559,7 +560,7 @@ matrix, where <span class="math notranslate nohighlight">\(N_m\)</span> is the n
 
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis">
-<span class="sig-name descname"><span class="pre">plot_just_analysis</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_weights_dict</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_just_analysis</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="Link to this definition">¶</a></dt>
 <dd><p>Visualizes the confusion matrix and the model wights for the
 justifiability analysis.</p>
 <section id="id13">
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.html b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.html
index 83a0521261114677d67c27b655eecf6180c73dad..0180e21c689d5ba3b4402ef9c463fbe1d7f0ea5f 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html b/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html
index 012f9ca7b1f4452085bbb1d49a37dc995a03c7ef..3eea32209da101a5e790589f865c4aa6e3ec5cbe 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.html b/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.html
index 3335850940b773ac5fb5ad777466f1be6e2d63fc..e21d3a79bb7e48b5b2217b9d0213985868e04a97 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.html b/public/_autosummary/bayesvalidrox.bayes_inference.html
index c7fdddf41ddfa00abc595774d5e201de4af10b93..11f98117146bca7bfacdc90d54d6de368db50aa8 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html b/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html
index 1c766909b66ee0fbeee63c3605370175ed825f8a..46c8c0469e8d6f67f613b1e201511c3e4abaf2ff 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -362,6 +363,32 @@ science, 5(1), pp.65-80.</p>
 <dl class="simple">
 <dt>BayesOpts<span class="classifier">obj</span></dt><dd><p>Bayes object.</p>
 </dd>
+<dt>engine<span class="classifier">bayesvalidrox.Engine</span></dt><dd><p>Engine object that contains the surrogate, model and expdesign</p>
+</dd>
+<dt>mcmc_params<span class="classifier">dict</span></dt><dd><p>Dictionary of parameters for the mcmc. Required are
+- init_samples
+- n_steps
+- n_walkers
+- n_burn
+- moves
+- multiplrocessing
+- verbose</p>
+</dd>
+<dt>Discrepancy<span class="classifier">bayesvalidrox.Discrepancy</span></dt><dd><p>Discrepancy object that described the uncertainty of the data.</p>
+</dd>
+</dl>
+<p>bias_inputs :</p>
+<p>error_model :</p>
+<p>req_outputs :</p>
+<p>selected_indices :</p>
+<p>emulator :</p>
+<dl class="simple">
+<dt>out_dir<span class="classifier">string</span></dt><dd><p>Directory to write the outputs to.</p>
+</dd>
+<dt>name<span class="classifier">string</span></dt><dd><p>Name of this MCMC selection (?)</p>
+</dd>
+<dt>BiasInputs<span class="classifier"></span></dt><dd><p>The default is None.</p>
+</dd>
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.bayes_inference.mcmc.MCMC.__init__">
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.gelman_rubin.html b/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.gelman_rubin.html
index d00bc5717899bfaeeff4c2839d4f6277d56ea7ea..69a4d24e107854fccbbfbc179d5eb9d793a6b7a8 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.gelman_rubin.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.gelman_rubin.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.html b/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.html
index 29b44ce99ee43c3613f96fa97f2bbdff3c0e6f26..2038b949523048507f6c3230e1bc1d86dc7ae10a 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.html b/public/_autosummary/bayesvalidrox.html
index 5c9c7d22e068d7b356e4b7f7f377a4aa656e5f35..75828bd7a5f89649705499369d2c7427093d1bf9 100644
--- a/public/_autosummary/bayesvalidrox.html
+++ b/public/_autosummary/bayesvalidrox.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.post_processing.html b/public/_autosummary/bayesvalidrox.post_processing.html
index ee8c181766d5eb03d89369af04eeff8cd7430279..56395e27e97e85fd5414731266521168c871ea7c 100644
--- a/public/_autosummary/bayesvalidrox.post_processing.html
+++ b/public/_autosummary/bayesvalidrox.post_processing.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.post_processing.post_processing.PostProcessing.html b/public/_autosummary/bayesvalidrox.post_processing.post_processing.PostProcessing.html
index 1e9cfdbeccd952605a0e0af15ea2bbc7674dc461..1bcb70f6927fe69b1be12fe2dd3c89aa01f6db09 100644
--- a/public/_autosummary/bayesvalidrox.post_processing.post_processing.PostProcessing.html
+++ b/public/_autosummary/bayesvalidrox.post_processing.post_processing.PostProcessing.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.post_processing.post_processing.html b/public/_autosummary/bayesvalidrox.post_processing.post_processing.html
index 1c0ee07983681c2921eb574305c332b34e5b33e1..585410977c9fc2990bf5023e3067b58c7ab883c0 100644
--- a/public/_autosummary/bayesvalidrox.post_processing.post_processing.html
+++ b/public/_autosummary/bayesvalidrox.post_processing.post_processing.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.pylink.html b/public/_autosummary/bayesvalidrox.pylink.html
index d3b4ddb9d22a55fa65b74b8480ed483ad79e5ebc..7637b34f3d664b546c8945bdb9ec6031abd92d8d 100644
--- a/public/_autosummary/bayesvalidrox.pylink.html
+++ b/public/_autosummary/bayesvalidrox.pylink.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html b/public/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html
index 868fd803201d3bf3f5b07955c8755ebf4ecd837f..bf9c611316356d523b3549447daf1098627b6f45 100644
--- a/public/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html
+++ b/public/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -339,7 +340,7 @@
 <h1>bayesvalidrox.pylink.pylink.PyLinkForwardModel<a class="headerlink" href="#bayesvalidrox-pylink-pylink-pylinkforwardmodel" title="Link to this heading">¶</a></h1>
 <dl class="py class">
 <dt class="sig sig-object py" id="bayesvalidrox.pylink.pylink.PyLinkForwardModel">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">bayesvalidrox.pylink.pylink.</span></span><span class="sig-name descname"><span class="pre">PyLinkForwardModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="Link to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">bayesvalidrox.pylink.pylink.</span></span><span class="sig-name descname"><span class="pre">PyLinkForwardModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">store</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out_dir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="Link to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>A forward model binder</p>
 <p>This calss serves as a code wrapper. This wrapper allows the execution of
@@ -428,7 +429,7 @@ This is only available for one output.</p>
 </dl>
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.pylink.pylink.PyLinkForwardModel.__init__">
-<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel.__init__" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">store</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out_dir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel.__init__" title="Link to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <p class="rubric">Methods</p>
diff --git a/public/_autosummary/bayesvalidrox.pylink.pylink.html b/public/_autosummary/bayesvalidrox.pylink.pylink.html
index fd29ae01185ad77c3ba5c349b2f79b87053dbe87..6c72ed7656f7f1af8a10d118aef4553b374c38f6 100644
--- a/public/_autosummary/bayesvalidrox.pylink.pylink.html
+++ b/public/_autosummary/bayesvalidrox.pylink.pylink.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.pylink.pylink.within_range.html b/public/_autosummary/bayesvalidrox.pylink.pylink.within_range.html
index d13e5d7afc4d30a74815716be03c5a653f7a8b2d..f5fe156616a2933fee2a7435f618159cf7bf9e00 100644
--- a/public/_autosummary/bayesvalidrox.pylink.pylink.within_range.html
+++ b/public/_autosummary/bayesvalidrox.pylink.pylink.within_range.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.adaptPlot.html b/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.adaptPlot.html
index 88166ae557a8ac4d2c5b58049ce6421b53f6da77..00c0b14a84a9171d1c90a97cdd954d78ba3e9e8e 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.adaptPlot.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.adaptPlot.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.html b/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.html
index dc183669e991009b0b317be369c56cfe4877392b..31ded85657492467d4814ceb77105ab9b3312ec9 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.apoly_construction.html b/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.apoly_construction.html
index 7fd894a2b05c2238263ca95d94ebe67ef701af04..cfa68525972b7938053f68e8eae4374aa9512cf5 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.apoly_construction.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.apoly_construction.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.html b/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.html
index bb8064c4ace44d3d188f6170d24d3752ab531710..48f07ba3f0ebf656ebeaedb6a2da36235e4a368e 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.BayesianLinearRegression.html b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.BayesianLinearRegression.html
index e3f16fb5c421af8aef20e6ad48e17acc12af2cc3..3dee9c9805fcccaebe781d3dad6c9c7e255a8d92 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.BayesianLinearRegression.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.BayesianLinearRegression.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.EBLinearRegression.html b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.EBLinearRegression.html
index 1e19d36659a9f0e61251e9a2df51a7390a84e03a..e5b8b3aaf10a2bd4c88f464582a0f1e5af901086 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.EBLinearRegression.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.EBLinearRegression.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.VBLinearRegression.html b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.VBLinearRegression.html
index 3ba8a66cb906826dceb78ad5e49f2025a5b042d7..49002d5f3ad44f76b604b9d87b280bf30604a146 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.VBLinearRegression.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.VBLinearRegression.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.gamma_mean.html b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.gamma_mean.html
index c3b2d56673133ba59dd38d065605a6d4e5a67186..f9446b9c30f385ca4ad6c1f66cfc05a3d9ed1c98 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.gamma_mean.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.gamma_mean.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.html b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.html
index 5d1164c23b955450a470d7b3109840c264c7255e..12a6923224ed1edd0db9a63ff0e4857f25b04495 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html b/public/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html
index d9bc2a754cec48165661ad78b544fd137effc6c1..bc8c4c8dff945dbb085793018c356b2b4b20320e 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -465,7 +466,7 @@ Run_No : int</p>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.engine.Engine.eval_metamodel">
-<span class="sig-name descname"><span class="pre">eval_metamodel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nsamples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sampling_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.engine.Engine.eval_metamodel" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">eval_metamodel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nsamples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sampling_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parallel</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.engine.Engine.eval_metamodel" title="Link to this definition">¶</a></dt>
 <dd><p>Evaluates metamodel at the requested samples. One can also generate
 nsamples.</p>
 <section id="id3">
@@ -481,6 +482,9 @@ default is None.</p>
 </dd>
 <dt>return_samples<span class="classifier">bool, optional</span></dt><dd><p>Retun samples, if no <cite>samples</cite> is provided. The default is False.</p>
 </dd>
+<dt>parallel<span class="classifier">bool, optional</span></dt><dd><p>Set to true if the evaluations should be done in parallel.
+The default is False.</p>
+</dd>
 </dl>
 </section>
 <section id="id4">
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.engine.hellinger_distance.html b/public/_autosummary/bayesvalidrox.surrogate_models.engine.hellinger_distance.html
index d4d269e7f964e73aedd4c9133b33fe1369c8039b..1468932d599cc45192028e30c4a3a7afb897a1f8 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.engine.hellinger_distance.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.engine.hellinger_distance.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.engine.html b/public/_autosummary/bayesvalidrox.surrogate_models.engine.html
index 885ebd13ab7642895d585e0c0567e2311e89b811..f43c214e2141ce0cf679c6be34d77fdfefb12c4f 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.engine.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.engine.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.engine.logpdf.html b/public/_autosummary/bayesvalidrox.surrogate_models.engine.logpdf.html
index d1ef23527311d72eb2e5481b01d677cc42b604d5..edd1833426247f70787c0adbf9956b4ab1214dca 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.engine.logpdf.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.engine.logpdf.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.engine.subdomain.html b/public/_autosummary/bayesvalidrox.surrogate_models.engine.subdomain.html
index 9e48ba3c35896e8bc02b49c37f91799ef5ab6363..6d630a95863555e36bed888f9b00ed6ffe0632d4 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.engine.subdomain.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.engine.subdomain.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule.html b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule.html
index cac4d998edd67a7ece45d79cb4b38b85af8d76c4..e081f64c34ee8f5cc6b6a8cf8014903ee8fb113c 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule_arbitrary.html b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule_arbitrary.html
index dde4517e0c995b2c29d94649c97c2c919b3a589a..936d75c876a538186eb06d729c8db840b4f48e51 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule_arbitrary.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule_arbitrary.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_univ_basis.html b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_univ_basis.html
index cc0f1d31cfbdd9bffc41e1755edfb2958379dde0..8a43256783ed04f6ab6d2c136c868a6a08473aa6 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_univ_basis.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_univ_basis.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.html b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.html
index 58709347de4066cf52315788d2b403067aed34e2..e566e9fc99989237f175a8313b24f228f845c8fa 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.poly_rec_coeffs.html b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.poly_rec_coeffs.html
index b13d05c48d065df1dcaea836b0d1ca9fcbdf9064..211d11ec9cebbbe03da83cb0cd51b11b0f2b0da2 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.poly_rec_coeffs.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.poly_rec_coeffs.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html b/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html
index 78f9787e11a1f9ebd7beac6d2f79d1f5dcc303b7..ebb205a5b7b266e9b1a0e311ec1acc8bf57d44ba 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -560,12 +561,12 @@ the MetaModel object.</p>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.init_param_space">
-<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.init_param_space" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.init_param_space" title="Link to this definition">¶</a></dt>
 <dd><p>Initializes parameter space.</p>
 <section id="id6">
 <h3>Parameters<a class="headerlink" href="#id6" title="Link to this heading">¶</a></h3>
 <dl class="simple">
-<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>None</cite>.</p>
+<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>1</cite>.</p>
 </dd>
 </dl>
 </section>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.check_ranges.html b/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.check_ranges.html
index c9556e4315c0343672ac2692d4c7b940a44de4d1..3f8c99c60c8dd63fa9a94a927f2e293699489f0a 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.check_ranges.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.check_ranges.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.html b/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.html
index 0a54834e033be55f36faa4bf9341ac15ce40fdf6..12f3e3b7b66a1370b00dc69415423fa565ed9b25 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.exploration.Exploration.html b/public/_autosummary/bayesvalidrox.surrogate_models.exploration.Exploration.html
index 4496b2d8f717108f8ae3821169740ccaeae2cbd7..bfc9e488793e12d2fb6ad190a3e9f763fcc99218 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.exploration.Exploration.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.exploration.Exploration.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.exploration.html b/public/_autosummary/bayesvalidrox.surrogate_models.exploration.html
index 5482569e1e7bd5a8e74fc2b8952952af366bd1d5..4fe52523a59bd299d130c541151d1ab08ee914c0 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.exploration.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.exploration.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.cross_truncate.html b/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.cross_truncate.html
index 5a03208c86819cc3e68adf1b35a9d5ac9c0ce90b..ef1e59d9f481edf25afe4cb78d250a75f1836ec9 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.cross_truncate.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.cross_truncate.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.glexindex.html b/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.glexindex.html
index a950df2ff0a2fc8f4c0aa58deb6e0e70982e5e70..128c4263055ecdbbcc5d460d2d56ea0d769d1c16 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.glexindex.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.glexindex.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.html b/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.html
index 96400f3335ee9fefce7b8c74b73b5d7b6540132d..f22f1237773177ce5762b38a38886c265b3ef192 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.html b/public/_autosummary/bayesvalidrox.surrogate_models.html
index 4312aa2528b5efb983f248efd68be7c01872f541..551916f8f3ec882453665ebd48bcc2b7323f3486 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html b/public/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html
index b5eb76fa2d343182c07caac085a2d114701e1ff4..f9d2df3bd39fc5c30cbc9d2128f7aed6e5e7bc29 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -417,12 +418,12 @@ the MetaModel object.</p>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.input_space.InputSpace.init_param_space">
-<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.input_space.InputSpace.init_param_space" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.input_space.InputSpace.init_param_space" title="Link to this definition">¶</a></dt>
 <dd><p>Initializes parameter space.</p>
 <section id="id2">
 <h3>Parameters<a class="headerlink" href="#id2" title="Link to this heading">¶</a></h3>
 <dl class="simple">
-<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>None</cite>.</p>
+<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>1</cite>.</p>
 </dd>
 </dl>
 </section>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.input_space.html b/public/_autosummary/bayesvalidrox.surrogate_models.input_space.html
index cc003dd63acb7bd7dff4be0e618139ff182668c7..7c8cd929947740190455750c4ad506dbc9f529dc 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.input_space.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.input_space.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Input.html b/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Input.html
index 95f8b8e450bb17bdf54da7c89e48b1e02dea8427..c3b3d9d99e6cb98532d79851949b7bba29ffd6db 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Input.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Input.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Marginal.html b/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Marginal.html
index fca0dcb0d866e58c0d2b0f1754daa5b673b05255..fcb16dad3f7ae7c501f6b1b30b0b795ad19d8bc1 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Marginal.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Marginal.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.inputs.html b/public/_autosummary/bayesvalidrox.surrogate_models.inputs.html
index d5c3b12c17f42351a7d5ce1b97793db0d014d893..4e16820e398f7ce11159e57c7b6a96aaf03160b5 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.inputs.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.inputs.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit.html b/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit.html
index 43f20bf429b54517e920f5cc4caad9ba94e71352..7e9829327c67c5f597d11b613427c8ff235d4705 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr.html b/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr.html
index 274d8319d15ce6f02bb11570b0f04de5d05ec170..8f61f3d066b8c15efb6f1dc676309ef43da0101c 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.html b/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.html
index f159c07b7d16bbea3883c98dccd211d0ce7e19a3..17f469e71810fd245e0abc4031a8ef2cbf00ced4 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD.html b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD.html
index 35ea14b81f33c21e5170f9ac5952fb87f1d38449..9dd1a74ff43fc63ee450278fb426515e5227df45 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.html b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.html
index f1a15392db7b92fd33289c6a80f192bf29ad688c..dcd0820e6d30a0bce8985938c8f7ad84dc0fbcf5 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions.html b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions.html
index ff1c030d120352eb3d7e6361764305295eb5ea81..05bcfb125d1a1b213e0db08d458290d7fef80fa1 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace.html b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace.html
index dc6b45be7b458da14c03fc147d90f0fc698b1eab..5ea393418ba57aac457d61fe83b4c22a18a98cb5 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.html b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.html
index 39bed6efb714b788a749f3800f756d641d8ab6d8..8ed5c18d58d878e5b16fcba867f0941b39449dff 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html
index 49744e8097ad29d88b38c04284f137b188ee2946..b19b796849a7a1500e42151901841e84e4dec613 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -449,8 +450,8 @@ For experimental design refer to <cite>InputSpace</cite>.</p>
 <tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.generate_polynomials" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.generate_polynomials"><code class="xref py py-obj docutils literal notranslate"><span class="pre">generate_polynomials</span></code></a>([max_deg])</p></td>
 <td><p>Generates (univariate) polynomials.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pca_transformation</span></code></a>(target[, verbose])</p></td>
-<td><p>Transforms the targets (outputs) via Principal Component Analysis</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pca_transformation</span></code></a>(target)</p></td>
+<td><p>Transforms the targets (outputs) via Principal Component Analysis.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.regression" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.regression"><code class="xref py py-obj docutils literal notranslate"><span class="pre">regression</span></code></a>(X, y, basis_indices[, ...])</p></td>
 <td><p>Fit regression using the regression method provided.</p></td>
@@ -720,16 +721,15 @@ The default is False.</p>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation">
-<span class="sig-name descname"><span class="pre">pca_transformation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="Link to this definition">¶</a></dt>
-<dd><p>Transforms the targets (outputs) via Principal Component Analysis</p>
+<span class="sig-name descname"><span class="pre">pca_transformation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="Link to this definition">¶</a></dt>
+<dd><p>Transforms the targets (outputs) via Principal Component Analysis.
+The number of features is set by <cite>self.n_pca_components</cite>.
+If this is not given, <cite>self.var_pca_threshold</cite> is used as a threshold.</p>
 <section id="id14">
 <h3>Parameters<a class="headerlink" href="#id14" title="Link to this heading">¶</a></h3>
 <dl class="simple">
 <dt>target<span class="classifier">array of shape (n_samples,)</span></dt><dd><p>Target values.</p>
 </dd>
-<dt>verbose<span class="classifier">bool</span></dt><dd><p>Set to True to get more information during functtion call.
-The default is False.</p>
-</dd>
 </dl>
 </section>
 <section id="id15">
@@ -804,7 +804,7 @@ for the fast version of the bootstrapping.</p>
 <section id="id20">
 <h3>Parameters<a class="headerlink" href="#id20" title="Link to this heading">¶</a></h3>
 <dl class="simple">
-<dt>X<span class="classifier">array of shape (n_samples, n_params)</span></dt><dd><p>Training set.</p>
+<dt>X<span class="classifier">array of shape (n_samples, n_params)</span></dt><dd><p>Training set. These samples should be already transformed.</p>
 </dd>
 <dt>y<span class="classifier">array of shape (n_samples, n_outs)</span></dt><dd><p>The (transformed) model responses.</p>
 </dd>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error.html b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error.html
index a047d2ad8298fa5a806499059658a45f4082a040..85883cb847cf1c65e2311dbcf9b1767ee88fd7f9 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.create_psi.html b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.create_psi.html
index 1b72a962cb784fc83d165f7b78c1ff34f2012271..4a66eb692ad6d7454d221ba2957f44131c9a5fe9 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.create_psi.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.create_psi.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator.html b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator.html
index 560f6c733c28d248e12526abe547a64accb91e9f..a38aa4e631828e0e30210cc27184f01c7b6072f1 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.html b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.html
index 82a65402e9c73ede08a4a8f24ca6a8bc459dbb98..bb5eaba6c656f8899f104b1832777061be31f5ed 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_sources/bayes_description.rst.txt b/public/_sources/bayes_description.rst.txt
index 2cfd3a6a8c43868b09f404eafdd36594ed9c3c7d..1c72a3e9987ca89da79132dece7ba4626a218e96 100644
--- a/public/_sources/bayes_description.rst.txt
+++ b/public/_sources/bayes_description.rst.txt
@@ -1,7 +1,90 @@
-Bayesian inference and multi-model comparison
-*********************************************
+Bayesian inference
+******************
+.. container:: twocol
 
+   .. container:: leftside
+   
+      With Bayesian inference we ask the question 'how does our understanding of the inputs change given some observation of the outputs of the model?', i.e. we perform an updating step of the prior distributions to posterior, based on some observations.
+      Bayesvalidrox provides a dedicated class to perform this task, :any:`bayesvalidrox.bayes_inference.bayes_inference.BayesInference`, which infers the posterior via ``rejection-sampling`` or ``MCMC``.
+      The likelihood in rejection sampling is estimated with the help of ``bootstrapping``.
+      MCMC-specific parameters are to be given as a dictionary called ``mcmc_params`` and can include 
+	  
+      * ``init_samples``: initial samples 
+      * ``n_steps``: number of steps 
+      * ``n_walkers``: number of walkers
+      * ``n_burn``: length of the burn-in 
+      * ``moves``: function to use for the moves, e.g. taken from ``emcee``
+      * ``multiprocessing``: setting for multiprocessing
+      * ``verbose``: verbosity 
+	  
+   .. container:: rightside
+   
+      .. image:: ../diagrams/bayesian_validation.png
+         :width: 300
+         :alt: UML diagram for classes related to Bayesian inference.
 
-.. image:: ../diagrams/bayesian_validation.png
-   :width: 300
-   :alt: UML diagram for classes related to Bayesian inference and multi-model comparison.
+The observation should be set as ``Model.observations`` in the ``Engine``, and an estimation of its uncertainty can be provided as a :any:`bayesvalidrox.bayes_inference.discrepancy.Discrepancy` object.
+
+Example
+=======
+For this example we need to add the following imports.
+
+>>> from bayesvalidrox import Discrepancy, BayesInference
+
+In order to run Bayesian inference we first need to provide an observation.
+For this example we take an evaluation of the model on some chosen sample and add the resulting values as ``Model.observations``.
+As this expects a 1D-array for each output key, we need to change the format slightly.
+
+>>> true_sample = [[2]]
+>>> observation = Model.run_model_parallel(true_sample)
+>>> Model.observations = {}
+>>> for key in observation:
+>>>     if key == 'x_values':
+>>>         Model.observations[key]=observation[key]
+>>>     else:
+>>>         Model.observations[key]=observation[key][0]
+
+Next we define the uncertainty on the observation with the class :any:`bayesvalidrox.bayes_inference.discrepancy.Discrepancy`.
+For this example we set the uncertainty to be zero-mean gaussian and dependent on the values in the observation, i.e. larger values have a larger uncertainty associated with them.
+The ``parameters`` contain the variance for each point in the observation.
+
+>>> obsData = pd.DataFrame(Model.observations, columns=Model.Output.names)
+>>> DiscrepancyOpts = Discrepancy('')
+>>> DiscrepancyOpts.type = 'Gaussian'
+>>> DiscrepancyOpts.parameters = obsData**2
+
+Now we can initialize an object of class :any:`bayesvalidrox.bayes_inference.bayes_inference.BayesInference` with all the wanted properties.
+This object has to be given our ``Engine``.
+If it should use the surrogate during inference, set ``emulator`` to ``True``, otherwise the model will be evaluated directly.
+We also set the defined ``Discrepancy``. and set ``post_plot_pred`` if posterior predictions should be visualized.
+
+>>> BayesObj = BayesInference(Engine_)
+>>> BayesObj.emulator = True
+>>> BayesObj.Discrepancy = DiscrepancyOpts
+>>> BayesObj.plot_post_pred = True
+
+In order to run with rejection sampling, we set the ``inference_method`` accordingly and add properties for ``bootstrap``.
+
+>>> BayesObj.inference_method = 'rejection'
+>>> BayesObj.bootstrap = True
+>>> BayesObj.n_bootstrap_itrs = 500
+>>> BayesObj.bootstrap_noise = 2
+
+If the sampling should be done with MCMC, then this is set as the ``inference_method`` and additional properties are given in ``mcmc_params``.
+For this example we use the python package ``emcee`` to define the MCMC moves.
+
+>>> BayesObj.inference_method = 'MCMC'
+>>> import emcee
+>>> BayesObj.mcmc_params = {
+>>>     'n_steps': 1e4,#5,
+>>>     'n_walkers': 30,
+>>>     'moves': emcee.moves.KDEMove(),
+>>>     'multiprocessing': False,
+>>>     'verbose': False
+>>>     }
+
+Then we run the inference.
+
+>>> BayesObj.create_inference()
+
+If the output directory ``BayesObj.out_dir`` is not set otherwise, the outputs are written into the folder ``
\ No newline at end of file
diff --git a/public/_sources/bmc_description.rst.txt b/public/_sources/bmc_description.rst.txt
new file mode 100644
index 0000000000000000000000000000000000000000..10e73bd1e819ad67df4fe48247a2bcf26fe698a7
--- /dev/null
+++ b/public/_sources/bmc_description.rst.txt
@@ -0,0 +1,7 @@
+Bayesian multi-model comparison
+*******************************
+
+.. image:: ../diagrams/bayesian_model_comparison.png
+   :width: 400
+   :alt: UML diagram for classes related to Bayesian multi-model comparison.
+
diff --git a/public/_sources/model_description.rst.txt b/public/_sources/model_description.rst.txt
index bb719886b9a5a61cfed3f44eebcf810b5ca46ef8..923f20a7cb126bf4f068f6f824c6ba0c6f0f9f42 100644
--- a/public/_sources/model_description.rst.txt
+++ b/public/_sources/model_description.rst.txt
@@ -6,10 +6,10 @@ Models
    .. container:: leftside
    
       BayesValidRox gives options to create interfaces for a variety of models with the class :any:`bayesvalidrox.pylink.pylink.PyLinkForwardModel`.
-	  Its main function is to run the model on given samples and to read in and contain MC references and observations.
+      Its main function is to run the model on given samples and to read in and contain MC references and observations.
 	  
-	  Models can be defined via python functions, shell commands or as general executables.
-	  This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.
+      Models can be defined via python functions, shell commands or as general executables.
+      This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.
 
    .. container:: rightside
    
diff --git a/public/_sources/packagedescription.rst.txt b/public/_sources/packagedescription.rst.txt
index f245959b8d5a4b1d56de4e9cc86cff64b2da9b98..1d1fd65173851b1c5942f7da35568c2fd3e4c696 100644
--- a/public/_sources/packagedescription.rst.txt
+++ b/public/_sources/packagedescription.rst.txt
@@ -69,3 +69,4 @@ The next pages lead through the topics given in BayesValidRox and describe the a
    al_description
    post_description
    bayes_description
+   bmc_description
diff --git a/public/_sources/post_description.rst.txt b/public/_sources/post_description.rst.txt
index af2172709f4581abfabdcfd06257edfa808aa501..987f18e7dbf8ea21cc987265bbbac7ac7a8d2ee1 100644
--- a/public/_sources/post_description.rst.txt
+++ b/public/_sources/post_description.rst.txt
@@ -4,11 +4,11 @@ Postprocessing
 
    .. container:: leftside
    
-         Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
-         The BayesValidRox class :any:`bayesvalidrox.post_processing.post_processing.PostProcessing` includes functions that are applicable to all types of surrogate model.
+      Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
+      The BayesValidRox class :any:`bayesvalidrox.post_processing.post_processing.PostProcessing` includes functions that are applicable to all types of surrogate model.
 		 
-		 * ``valid_metamodel``: visualizing some metamodel runs against the corresponding model runs
-		 * ``check_accuracy``: computing the RMSE error of the surrogate model
+      * ``valid_metamodel``: visualizing some metamodel runs against the corresponding model runs
+      * ``check_accuracy``: computing the RMSE error of the surrogate model
 		 
    .. container:: rightside
 
diff --git a/public/al_description.html b/public/al_description.html
index 78a5f609efb6ef18b9a5cf743e0927f79504fb15..e3cde5ecdeba4d96aa5f5ae5687880f353b4cfdb 100644
--- a/public/al_description.html
+++ b/public/al_description.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/analyticalfunction.html b/public/analyticalfunction.html
index 42509cf3862f35bffb524e96a08c1519f3cd6267..799f0350ab63fcff73326e688d496645156564eb 100644
--- a/public/analyticalfunction.html
+++ b/public/analyticalfunction.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/api.html b/public/api.html
index d853aff4e2794fdef4103a72a3b981e1acafc568..7f918265aaa46ff4fce912683b613ad2fe00c692 100644
--- a/public/api.html
+++ b/public/api.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/bayes_description.html b/public/bayes_description.html
index 62bb18a5a39b10a142d3caf25cd09dea371f6d75..7a933926610a356faf87a0da0f856ea8e2340d7b 100644
--- a/public/bayes_description.html
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@@ -3,10 +3,10 @@
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 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
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+<li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
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-          <section id="bayesian-inference-and-multi-model-comparison">
-<h1>Bayesian inference and multi-model comparison<a class="headerlink" href="#bayesian-inference-and-multi-model-comparison" title="Link to this heading">¶</a></h1>
-<a class="reference internal image-reference" href="_images/bayesian_validation.png"><img alt="UML diagram for classes related to Bayesian inference and multi-model comparison." src="_images/bayesian_validation.png" style="width: 300px;" /></a>
+          <section id="bayesian-inference">
+<h1>Bayesian inference<a class="headerlink" href="#bayesian-inference" title="Link to this heading">¶</a></h1>
+<div class="twocol docutils container">
+<div class="leftside docutils container">
+<p>With Bayesian inference we ask the question ‘how does our understanding of the inputs change given some observation of the outputs of the model?’, i.e. we perform an updating step of the prior distributions to posterior, based on some observations.
+Bayesvalidrox provides a dedicated class to perform this task, <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html#bayesvalidrox.bayes_inference.bayes_inference.BayesInference" title="bayesvalidrox.bayes_inference.bayes_inference.BayesInference"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.bayes_inference.BayesInference</span></code></a>, which infers the posterior via <code class="docutils literal notranslate"><span class="pre">rejection-sampling</span></code> or <code class="docutils literal notranslate"><span class="pre">MCMC</span></code>.
+The likelihood in rejection sampling is estimated with the help of <code class="docutils literal notranslate"><span class="pre">bootstrapping</span></code>.
+MCMC-specific parameters are to be given as a dictionary called <code class="docutils literal notranslate"><span class="pre">mcmc_params</span></code> and can include</p>
+<ul class="simple">
+<li><p><code class="docutils literal notranslate"><span class="pre">init_samples</span></code>: initial samples</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">n_steps</span></code>: number of steps</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">n_walkers</span></code>: number of walkers</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">n_burn</span></code>: length of the burn-in</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">moves</span></code>: function to use for the moves, e.g. taken from <code class="docutils literal notranslate"><span class="pre">emcee</span></code></p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">multiprocessing</span></code>: setting for multiprocessing</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">verbose</span></code>: verbosity</p></li>
+</ul>
+</div>
+<div class="rightside docutils container">
+<a class="reference internal image-reference" href="_images/bayesian_validation.png"><img alt="UML diagram for classes related to Bayesian inference." src="_images/bayesian_validation.png" style="width: 300px;" /></a>
+</div>
+</div>
+<p>The observation should be set as <code class="docutils literal notranslate"><span class="pre">Model.observations</span></code> in the <code class="docutils literal notranslate"><span class="pre">Engine</span></code>, and an estimation of its uncertainty can be provided as a <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html#bayesvalidrox.bayes_inference.discrepancy.Discrepancy" title="bayesvalidrox.bayes_inference.discrepancy.Discrepancy"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.discrepancy.Discrepancy</span></code></a> object.</p>
+<section id="example">
+<h2>Example<a class="headerlink" href="#example" title="Link to this heading">¶</a></h2>
+<p>For this example we need to add the following imports.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">bayesvalidrox</span> <span class="kn">import</span> <span class="n">Discrepancy</span><span class="p">,</span> <span class="n">BayesInference</span>
+</pre></div>
+</div>
+<p>In order to run Bayesian inference we first need to provide an observation.
+For this example we take an evaluation of the model on some chosen sample and add the resulting values as <code class="docutils literal notranslate"><span class="pre">Model.observations</span></code>.
+As this expects a 1D-array for each output key, we need to change the format slightly.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">true_sample</span> <span class="o">=</span> <span class="p">[[</span><span class="mi">2</span><span class="p">]]</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">observation</span> <span class="o">=</span> <span class="n">Model</span><span class="o">.</span><span class="n">run_model_parallel</span><span class="p">(</span><span class="n">true_sample</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">Model</span><span class="o">.</span><span class="n">observations</span> <span class="o">=</span> <span class="p">{}</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">observation</span><span class="p">:</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="k">if</span> <span class="n">key</span> <span class="o">==</span> <span class="s1">&#39;x_values&#39;</span><span class="p">:</span>
+<span class="gp">&gt;&gt;&gt; </span>        <span class="n">Model</span><span class="o">.</span><span class="n">observations</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">=</span><span class="n">observation</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="k">else</span><span class="p">:</span>
+<span class="gp">&gt;&gt;&gt; </span>        <span class="n">Model</span><span class="o">.</span><span class="n">observations</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">=</span><span class="n">observation</span><span class="p">[</span><span class="n">key</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
+</pre></div>
+</div>
+<p>Next we define the uncertainty on the observation with the class <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html#bayesvalidrox.bayes_inference.discrepancy.Discrepancy" title="bayesvalidrox.bayes_inference.discrepancy.Discrepancy"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.discrepancy.Discrepancy</span></code></a>.
+For this example we set the uncertainty to be zero-mean gaussian and dependent on the values in the observation, i.e. larger values have a larger uncertainty associated with them.
+The <code class="docutils literal notranslate"><span class="pre">parameters</span></code> contain the variance for each point in the observation.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">obsData</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">Model</span><span class="o">.</span><span class="n">observations</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="n">Model</span><span class="o">.</span><span class="n">Output</span><span class="o">.</span><span class="n">names</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">DiscrepancyOpts</span> <span class="o">=</span> <span class="n">Discrepancy</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">DiscrepancyOpts</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="s1">&#39;Gaussian&#39;</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">DiscrepancyOpts</span><span class="o">.</span><span class="n">parameters</span> <span class="o">=</span> <span class="n">obsData</span><span class="o">**</span><span class="mi">2</span>
+</pre></div>
+</div>
+<p>Now we can initialize an object of class <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html#bayesvalidrox.bayes_inference.bayes_inference.BayesInference" title="bayesvalidrox.bayes_inference.bayes_inference.BayesInference"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.bayes_inference.BayesInference</span></code></a> with all the wanted properties.
+This object has to be given our <code class="docutils literal notranslate"><span class="pre">Engine</span></code>.
+If it should use the surrogate during inference, set <code class="docutils literal notranslate"><span class="pre">emulator</span></code> to <code class="docutils literal notranslate"><span class="pre">True</span></code>, otherwise the model will be evaluated directly.
+We also set the defined <code class="docutils literal notranslate"><span class="pre">Discrepancy</span></code>. and set <code class="docutils literal notranslate"><span class="pre">post_plot_pred</span></code> if posterior predictions should be visualized.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span> <span class="o">=</span> <span class="n">BayesInference</span><span class="p">(</span><span class="n">Engine_</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">emulator</span> <span class="o">=</span> <span class="kc">True</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">Discrepancy</span> <span class="o">=</span> <span class="n">DiscrepancyOpts</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">plot_post_pred</span> <span class="o">=</span> <span class="kc">True</span>
+</pre></div>
+</div>
+<p>In order to run with rejection sampling, we set the <code class="docutils literal notranslate"><span class="pre">inference_method</span></code> accordingly and add properties for <code class="docutils literal notranslate"><span class="pre">bootstrap</span></code>.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">inference_method</span> <span class="o">=</span> <span class="s1">&#39;rejection&#39;</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">bootstrap</span> <span class="o">=</span> <span class="kc">True</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">n_bootstrap_itrs</span> <span class="o">=</span> <span class="mi">500</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">bootstrap_noise</span> <span class="o">=</span> <span class="mi">2</span>
+</pre></div>
+</div>
+<p>If the sampling should be done with MCMC, then this is set as the <code class="docutils literal notranslate"><span class="pre">inference_method</span></code> and additional properties are given in <code class="docutils literal notranslate"><span class="pre">mcmc_params</span></code>.
+For this example we use the python package <code class="docutils literal notranslate"><span class="pre">emcee</span></code> to define the MCMC moves.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">inference_method</span> <span class="o">=</span> <span class="s1">&#39;MCMC&#39;</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">emcee</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">mcmc_params</span> <span class="o">=</span> <span class="p">{</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="s1">&#39;n_steps&#39;</span><span class="p">:</span> <span class="mf">1e4</span><span class="p">,</span><span class="c1">#5,</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="s1">&#39;n_walkers&#39;</span><span class="p">:</span> <span class="mi">30</span><span class="p">,</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="s1">&#39;moves&#39;</span><span class="p">:</span> <span class="n">emcee</span><span class="o">.</span><span class="n">moves</span><span class="o">.</span><span class="n">KDEMove</span><span class="p">(),</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="s1">&#39;multiprocessing&#39;</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="s1">&#39;verbose&#39;</span><span class="p">:</span> <span class="kc">False</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="p">}</span>
+</pre></div>
+</div>
+<p>Then we run the inference.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">create_inference</span><span class="p">()</span>
+</pre></div>
+</div>
+<p>If the output directory <code class="docutils literal notranslate"><span class="pre">BayesObj.out_dir</span></code> is not set otherwise, the outputs are written into the folder ``</p>
+</section>
 </section>
 
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@@ -345,12 +430,12 @@
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diff --git a/public/beam.html b/public/beam.html
index 6c82f54b9c2f2bca66cd21adf154c9aa11a04319..64c4a4c02961b651df6c1cc9c11ae1648000a38b 100644
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@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
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+<li class="toctree-l4 has-children"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.input_space.html">bayesvalidrox.surrogate_models.input_space</a><input class="toctree-checkbox" id="toctree-checkbox-23" name="toctree-checkbox-23" role="switch" type="checkbox"/><label for="toctree-checkbox-23"><div class="visually-hidden">Toggle navigation of bayesvalidrox.surrogate_models.input_space</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html">bayesvalidrox.surrogate_models.input_space.InputSpace</a></li>
+</ul>
+</li>
+<li class="toctree-l4 has-children"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.inputs.html">bayesvalidrox.surrogate_models.inputs</a><input class="toctree-checkbox" id="toctree-checkbox-24" name="toctree-checkbox-24" role="switch" type="checkbox"/><label for="toctree-checkbox-24"><div class="visually-hidden">Toggle navigation of bayesvalidrox.surrogate_models.inputs</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.inputs.Input.html">bayesvalidrox.surrogate_models.inputs.Input</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.inputs.Marginal.html">bayesvalidrox.surrogate_models.inputs.Marginal</a></li>
+</ul>
+</li>
+<li class="toctree-l4 has-children"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.html">bayesvalidrox.surrogate_models.orthogonal_matching_pursuit</a><input class="toctree-checkbox" id="toctree-checkbox-25" name="toctree-checkbox-25" role="switch" type="checkbox"/><label for="toctree-checkbox-25"><div class="visually-hidden">Toggle navigation of bayesvalidrox.surrogate_models.orthogonal_matching_pursuit</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr.html">bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit.html">bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit</a></li>
+</ul>
+</li>
+<li class="toctree-l4 has-children"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.html">bayesvalidrox.surrogate_models.reg_fast_ard</a><input class="toctree-checkbox" id="toctree-checkbox-26" name="toctree-checkbox-26" role="switch" type="checkbox"/><label for="toctree-checkbox-26"><div class="visually-hidden">Toggle navigation of bayesvalidrox.surrogate_models.reg_fast_ard</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions.html">bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD.html">bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD</a></li>
+</ul>
+</li>
+<li class="toctree-l4 has-children"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.html">bayesvalidrox.surrogate_models.reg_fast_laplace</a><input class="toctree-checkbox" id="toctree-checkbox-27" name="toctree-checkbox-27" role="switch" type="checkbox"/><label for="toctree-checkbox-27"><div class="visually-hidden">Toggle navigation of bayesvalidrox.surrogate_models.reg_fast_laplace</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace.html">bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace</a></li>
+</ul>
+</li>
+<li class="toctree-l4 has-children"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.html">bayesvalidrox.surrogate_models.surrogate_models</a><input class="toctree-checkbox" id="toctree-checkbox-28" name="toctree-checkbox-28" role="switch" type="checkbox"/><label for="toctree-checkbox-28"><div class="visually-hidden">Toggle navigation of bayesvalidrox.surrogate_models.surrogate_models</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error.html">bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.create_psi.html">bayesvalidrox.surrogate_models.surrogate_models.create_psi</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator.html">bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html">bayesvalidrox.surrogate_models.surrogate_models.MetaModel</a></li>
+</ul>
+</li>
+</ul>
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+          <section id="bayesian-multi-model-comparison">
+<h1>Bayesian multi-model comparison<a class="headerlink" href="#bayesian-multi-model-comparison" title="Link to this heading">¶</a></h1>
+<a class="reference internal image-reference" href="_images/bayesian_model_comparison.png"><img alt="UML diagram for classes related to Bayesian multi-model comparison." src="_images/bayesian_model_comparison.png" style="width: 400px;" /></a>
+</section>
+
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diff --git a/public/borehole.html b/public/borehole.html
index eafbe8618ff8d0757196ae0777a1cf723a5fffbe..683c27d0e04ec78a166d826a129aac151452cda5 100644
--- a/public/borehole.html
+++ b/public/borehole.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/examples.html b/public/examples.html
index 9d6b6cce855166cfe6ef716ab177457dbfa207cc..4c621310a3263574de929c0bdd7f0468c73256fb 100644
--- a/public/examples.html
+++ b/public/examples.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/genindex.html b/public/genindex.html
index 2b0791a3b4af33fa58bd71d15659bc6600d809eb..67a702598c7ef269e4c7bd789daf188a8d2611a0 100644
--- a/public/genindex.html
+++ b/public/genindex.html
@@ -168,7 +168,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/index.html b/public/index.html
index 460cf3cb78de9b9cd652a03cf2a89b74f44b34af..dcad29fd053e5f804ccff50405434996036a710f 100644
--- a/public/index.html
+++ b/public/index.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/input_description.html b/public/input_description.html
index 39e16d2b9c9ebbb21b05daa969ec7defe54b2f01..15276ff89db8a4735a131a0ee6fd8defc947bba0 100644
--- a/public/input_description.html
+++ b/public/input_description.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/ishigami.html b/public/ishigami.html
index 06d5b7d8c9adcb37841b53c2a5e31c6cdb19a142..dcf8bda0beb013af407cfc2bc09692aa9e5f66e9 100644
--- a/public/ishigami.html
+++ b/public/ishigami.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/model_description.html b/public/model_description.html
index 2dbaeed956d41cede70ba75d52434aab60a16698..da41e466709a96f632cca9cccb79f6e51e129f7f 100644
--- a/public/model_description.html
+++ b/public/model_description.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -339,12 +340,10 @@
 <h1>Models<a class="headerlink" href="#models" title="Link to this heading">¶</a></h1>
 <div class="twocol docutils container">
 <div class="leftside docutils container">
-<dl>
-<dt>BayesValidRox gives options to create interfaces for a variety of models with the class <a class="reference internal" href="_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="bayesvalidrox.pylink.pylink.PyLinkForwardModel"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.pylink.pylink.PyLinkForwardModel</span></code></a>.</dt><dd><p>Its main function is to run the model on given samples and to read in and contain MC references and observations.</p>
+<p>BayesValidRox gives options to create interfaces for a variety of models with the class <a class="reference internal" href="_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="bayesvalidrox.pylink.pylink.PyLinkForwardModel"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.pylink.pylink.PyLinkForwardModel</span></code></a>.
+Its main function is to run the model on given samples and to read in and contain MC references and observations.</p>
 <p>Models can be defined via python functions, shell commands or as general executables.
 This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.</p>
-</dd>
-</dl>
 </div>
 <div class="rightside docutils container">
 <a class="reference internal image-reference" href="_images/model.png"><img alt="UML diagram for the bayesvalidrox class :any:`bayesvalidrox.pylink.pylink.PyLinkForwardModel`." src="_images/model.png" style="width: 150px;" /></a>
diff --git a/public/modelcomparison.html b/public/modelcomparison.html
index 723a66ed173227b1716a63d607f17305a2b44e17..472be01bb69119cbebd70a3d8d3d1a7eee0e5028 100644
--- a/public/modelcomparison.html
+++ b/public/modelcomparison.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/objects.inv b/public/objects.inv
index b24151365f5b50ce51d7b5ed10cfdff340f22cf1..9269935a85e887aac2b1b3f13b91a4a9385002b6 100644
Binary files a/public/objects.inv and b/public/objects.inv differ
diff --git a/public/ohaganfunction.html b/public/ohaganfunction.html
index cfe645ff03aebcd76205c1fc126f95d245425524..e7b7558755f9fd027a76475797e0e6836f331103 100644
--- a/public/ohaganfunction.html
+++ b/public/ohaganfunction.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/packagedescription.html b/public/packagedescription.html
index c76923ed2587b0b106908c8890e2adb48ed50353..875119c2724b77d8943b9bd3cb9f76be9c293d0e 100644
--- a/public/packagedescription.html
+++ b/public/packagedescription.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -382,7 +383,8 @@ If multiple (surrogate) models are given, they can be compared against each othe
 <li class="toctree-l1"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l1"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l1"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l1"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l1"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l1"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </div>
 </section>
diff --git a/public/pollution.html b/public/pollution.html
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         <title>Postprocessing - bayesvalidrox 1.0.0 documentation</title>
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 <p>Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
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\ No newline at end of file
diff --git a/public/surrogate_description.html b/public/surrogate_description.html
index c48db82a4773b839e34ca20dce1c610bb97ffb3a..db4708ce672e7ec6bdb91614f5e36b2b7aabec9a 100644
--- a/public/surrogate_description.html
+++ b/public/surrogate_description.html
@@ -170,7 +170,8 @@
 <li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/tutorial.html b/public/tutorial.html
index 820f6d348870c77e961ce0e23f2158a2279322da..f4c9412913a544299343f5beb0e73c9ed9800d0d 100644
--- a/public/tutorial.html
+++ b/public/tutorial.html
@@ -3,7 +3,7 @@
   <head><meta charset="utf-8"/>
     <meta name="viewport" content="width=device-width,initial-scale=1"/>
     <meta name="color-scheme" content="light dark"><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
-<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="EXAMPLES" href="examples.html" /><link rel="prev" title="Bayesian inference and multi-model comparison" href="bayes_description.html" />
+<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="EXAMPLES" href="examples.html" /><link rel="prev" title="Bayesian multi-model comparison" href="bmc_description.html" />
 
     <!-- Generated with Sphinx 7.3.7 and Furo 2023.09.10 -->
         <title>TUTORIAL - bayesvalidrox 1.0.0 documentation</title>
@@ -170,7 +170,8 @@
 <li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
 <li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
 <li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
 </ul>
 </li>
 <li class="toctree-l1 current current-page"><a class="current reference internal" href="#">TUTORIAL</a></li>
@@ -596,7 +597,7 @@ The method <code class="docutils literal notranslate"><span class="pre">sobolInd
 </div>
 <p>If we set <code class="docutils literal notranslate"><span class="pre">emulator</span></code> to be true the Bayesian Inference will be performed based on the emulator.
 Some posterior predictions will be plotted by setting <code class="docutils literal notranslate"><span class="pre">plot_post_pred</span></code>.
-More options for Bayesian inference are listed at <a class="reference internal" href="bayes_description.html"><span class="doc">Bayesian inference and multi-model comparison</span></a>.</p>
+More options for Bayesian inference are listed at <a class="reference internal" href="bayes_description.html"><span class="doc">Bayesian inference</span></a>.</p>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
 <p>Setting <code class="docutils literal notranslate"><span class="pre">emulator</span> <span class="pre">=</span> <span class="pre">False</span></code> means that the inference is based on actual model runs and not the surrogate.
@@ -694,14 +695,14 @@ plots of posterior predictions if wanted.</p>
               </div>
               <svg class="furo-related-icon"><use href="#svg-arrow-right"></use></svg>
             </a>
-          <a class="prev-page" href="bayes_description.html">
+          <a class="prev-page" href="bmc_description.html">
               <svg class="furo-related-icon"><use href="#svg-arrow-right"></use></svg>
               <div class="page-info">
                 <div class="context">
                   <span>Previous</span>
                 </div>
                 
-                <div class="title">Bayesian inference and multi-model comparison</div>
+                <div class="title">Bayesian multi-model comparison</div>
                 
               </div>
             </a>