DOC Move some examples into subfolders.

Author: twiecki

docs/source/examples.rst

@@ -8,25 +8,40 @@ Examples
    notebooks/BEST.ipynb
    notebooks/LKJ.ipynb
    notebooks/stochastic_volatility.ipynb
+   notebooks/pmf-pymc.ipynb
+   notebooks/rugby_analytics.ipynb
+   notebooks/survival_analysis.ipynb
+   notebooks/posterior_predictive.ipynb
+   notebooks/GP-smoothing.ipynb
+   notebooks/howto_debugging.ipynb
+ 
+GLM
+===
+
+.. toctree::
    notebooks/GLM-linear.ipynb
    notebooks/GLM-robust.ipynb
    notebooks/GLM-robust-with-outlier-detection.ipynb
    notebooks/GLM-model-selection.ipynb
    notebooks/GLM-rolling-regression.ipynb
    notebooks/GLM-logistic.ipynb
    notebooks/GLM-hierarchical.ipynb
+   notebooks/GLM-poisson-regression.ipynb
+
+ADVI
+====
+
+.. toctree::
    notebooks/GLM-hierarchical-ADVI.ipynb
    notebooks/GLM-hierarchical-advi-minibatch.ipynb
-   notebooks/GLM-poisson-regression.ipynb
-   notebooks/pmf-pymc.ipynb
-   notebooks/rugby_analytics.ipynb
-   notebooks/posterior_predictive.ipynb
-   notebooks/survival_analysis.ipynb
-   notebooks/GP-smoothing.ipynb
-   notebooks/Bayesian_LogReg.ipynb
-   notebooks/dp_mix.ipynb
-   notebooks/bayesian_neural_network_advi.ipynb
    notebooks/lda-advi-aevb.ipynb
+   notebooks/bayesian_neural_network_advi.ipynb
+
+Mixture Models
+==============
+
+.. toctree::
    notebooks/gaussian_mixture_model.ipynb
    notebooks/gaussian-mixture-model-advi.ipynb
-   notebooks/howto_debugging.ipynb
+   notebooks/dp_mix.ipynb
+

docs/source/notebooks/GLM-hierarchical-ADVI.ipynb

@@ -206,9 +206,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Posterior Predictive Check\n",
+    "## Posterior Predictive Check\n",
     "\n",
-    "## The Root Mean Square Deviation\n",
+    "### The Root Mean Square Deviation\n",
     "\n",
     "To find out which of the models explains the data better we can calculate the Root Mean Square Deviaton (RMSD). This posterior predictive check revolves around recreating the data based on the parameters found at different moments in the chain. The recreated or predicted values are subsequently compared to the real data points, the model that predicts data points closer to the original data is considered the better one. Thus, the lower the RMSD the better.\n",
     "\n",

docs/source/notebooks/gaussian_mixture_model.ipynb

@@ -1,5 +1,14 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Gaussian Mixture Model\n",
+    "\n",
+    "Original NB by Abe Flaxman, modified by Thomas Wiecki\n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -23,15 +32,6 @@
     "sns.set_style('darkgrid')"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Mixture Model in PyMC3\n",
-    "\n",
-    "Original NB by Abe Flaxman, modified by Thomas Wiecki\n"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -321,8 +321,9 @@
   }
  ],
  "metadata": {
+  "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python [default]",
    "language": "python",
    "name": "python3"
   },

docs/source/notebooks/survival_analysis.ipynb

@@ -10,7 +10,7 @@
     "\n",
     "[Survival analysis](https://en.wikipedia.org/wiki/Survival_analysis) studies the distribution of the time to an event.  Its applications span many fields across medicine, biology, engineering, and social science.  This tutorial shows how to fit and analyze a Bayesian survival model in Python using [PyMC3](https://pymc-devs.github.io/pymc3).\n",
     "\n",
-    "We illustrate these concepts by analyzing a [mastectomy data set](https://vincentarelbundock.github.io/Rdatasets/doc/HSAUR/mastectomy.html) from `R`'s [`HSAUR`](https://cran.r-project.org/web/packages/HSAUR/index.html) package."
+    "We illustrate these concepts by analyzing a [mastectomy data set](https://vincentarelbundock.github.io/Rdatasets/doc/HSAUR/mastectomy.html) from `R`'s [HSAUR](https://cran.r-project.org/web/packages/HSAUR/index.html) package."
    ]
   },
   {
@@ -53,7 +53,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Fortunately, [`statsmodels.datasets`](http://statsmodels.sourceforge.net/0.6.0/datasets/index.html) makes it quite easy to load a number of data sets from `R`."
+    "Fortunately, [statsmodels.datasets](http://statsmodels.sourceforge.net/0.6.0/datasets/index.html) makes it quite easy to load a number of data sets from `R`."
    ]
   },
   {
@@ -968,8 +968,9 @@
   }
  ],
  "metadata": {
+  "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python [default]",
    "language": "python",
    "name": "python3"
   },
@@ -983,7 +984,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.5.2"
   }
  },
  "nbformat": 4,