started MCMC chapter in BM4H

Emaasit · Nov 13, 2017 · 10ace7b · 10ace7b
1 parent 472fbf0
commit 10ace7b
Show file tree

Hide file tree

Showing 8 changed files with 3,752 additions and 14 deletions.
diff --git a/.ipynb_checkpoints/01_quick_start-checkpoint.ipynb b/.ipynb_checkpoints/01_quick_start-checkpoint.ipynb
@@ -89,7 +89,10 @@
     "    \n",
     "    # the likelihood of observations\n",
     "    # data can be passed in as ndarray or pandas df\n",
-    "    obs = pm.Normal('obs', mu = mu, sd = sd, observed = y)"
+    "    obs = pm.Normal('obs', mu = mu, sd = sd, observed = y)\n",
+    "    \n",
+    "     # simulate data from model\n",
+    "    simulated_obs = pm.Normal(\"simulated_obs\", mu = mu, sd = sd, shape = mu.tag.test_value.shape)"
    ]
   },
   {
@@ -618,6 +621,17 @@
     "posterior.get_values('mu', chains = 1).shape # get values of a single chain"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# extract the simulated data\n",
+    "simulated_data = posterior[\"simulated_obs\"]\n",
+    "simulated_data.shape"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -3435,7 +3449,10 @@
     "    mu = pm.Normal(\"mu\", mu = 0, sd = 1e6)\n",
     "       \n",
     "    ## specify the likelihood\n",
-    "    obs = pm.Normal(\"obs\", mu = mu, sd = sigma, observed = y)"
+    "    obs = pm.Normal(\"obs\", mu = mu, sd = sigma, observed = y)\n",
+    "    \n",
+    "    # simulate data from model\n",
+    "    simulated_obs = pm.Normal(\"simulated_obs\", mu = mu, sd = sigma, shape = mu.tag.test_value.shape)"
    ]
   },
   {
@@ -3675,7 +3692,10 @@
     "    theta = pm.Deterministic(\"theta\", mu + tau*eta)\n",
     "    \n",
     "    ## specify the likelihood\n",
-    "    obs = pm.Normal(\"obs\", mu = theta, sd = sigma, observed = y)"
+    "    obs = pm.Normal(\"obs\", mu = theta, sd = sigma, observed = y)\n",
+    "    \n",
+    "    # simulate data from model\n",
+    "    simulated_obs = pm.Normal(\"simulated_obs\", mu = theta, sd = sigma, shape = theta.tag.test_value.shape)"
    ]
   },
   {
@@ -4244,6 +4264,17 @@
     "pm.summary(posterior_schools, varnames = [\"theta\", \"mu\", \"tau\"])"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# extract the simulated data\n",
+    "simulated_data = posterior[\"simulated_obs\"]\n",
+    "simulated_data.shape"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/01_quick_start.ipynb b/01_quick_start.ipynb
@@ -89,7 +89,10 @@
     "    \n",
     "    # the likelihood of observations\n",
     "    # data can be passed in as ndarray or pandas df\n",
-    "    obs = pm.Normal('obs', mu = mu, sd = sd, observed = y)"
+    "    obs = pm.Normal('obs', mu = mu, sd = sd, observed = y)\n",
+    "    \n",
+    "     # simulate data from model\n",
+    "    simulated_obs = pm.Normal(\"simulated_obs\", mu = mu, sd = sd, shape = mu.tag.test_value.shape)"
    ]
   },
   {
@@ -618,6 +621,17 @@
     "posterior.get_values('mu', chains = 1).shape # get values of a single chain"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# extract the simulated data\n",
+    "simulated_data = posterior[\"simulated_obs\"]\n",
+    "simulated_data.shape"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -3435,7 +3449,10 @@
     "    mu = pm.Normal(\"mu\", mu = 0, sd = 1e6)\n",
     "       \n",
     "    ## specify the likelihood\n",
-    "    obs = pm.Normal(\"obs\", mu = mu, sd = sigma, observed = y)"
+    "    obs = pm.Normal(\"obs\", mu = mu, sd = sigma, observed = y)\n",
+    "    \n",
+    "    # simulate data from model\n",
+    "    simulated_obs = pm.Normal(\"simulated_obs\", mu = mu, sd = sigma, shape = mu.tag.test_value.shape)"
    ]
   },
   {
@@ -3675,7 +3692,10 @@
     "    theta = pm.Deterministic(\"theta\", mu + tau*eta)\n",
     "    \n",
     "    ## specify the likelihood\n",
-    "    obs = pm.Normal(\"obs\", mu = theta, sd = sigma, observed = y)"
+    "    obs = pm.Normal(\"obs\", mu = theta, sd = sigma, observed = y)\n",
+    "    \n",
+    "    # simulate data from model\n",
+    "    simulated_obs = pm.Normal(\"simulated_obs\", mu = theta, sd = sigma, shape = theta.tag.test_value.shape)"
    ]
   },
   {
@@ -4244,6 +4264,17 @@
     "pm.summary(posterior_schools, varnames = [\"theta\", \"mu\", \"tau\"])"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# extract the simulated data\n",
+    "simulated_data = posterior[\"simulated_obs\"]\n",
+    "simulated_data.shape"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/bm4h/.ipynb_checkpoints/ch02_more_pymc-checkpoint.ipynb b/bm4h/.ipynb_checkpoints/ch02_more_pymc-checkpoint.ipynb
diff --git a/bm4h/.ipynb_checkpoints/ch03_intro_mcmc-checkpoint.ipynb b/bm4h/.ipynb_checkpoints/ch03_intro_mcmc-checkpoint.ipynb
@@ -0,0 +1,39 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Introduction to MCMC"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/bm4h/.ipynb_checkpoints/distplot-checkpoint.png b/bm4h/.ipynb_checkpoints/distplot-checkpoint.png