Complex distribution example

Complex_distribution_example_PyMC.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Arm_B\n",
      "23.632045646\n"
     ]
    },
    {
     "data": {
      "image/png": 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YsGDY/Uqlkq6urvT29mbChAnp7OzM9OnTz9h3w4YNefLJJ9PY2JgpU6aks7Mz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11cae3940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Arm_C\n",
      "22.3993879508\n"
     ]
    },
    {
     "data": {
      "image/png": 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AAAAo1FjvAgBgvDtxx801jWvY+MQYVwIAAPVjJRIAAAAAhaxEAoBRYsUSAADn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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ca84c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Arm_A\n",
      "20.279012554\n"
     ]
    },
    {
     "data": {
      "image/png": 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W1jZ+3dbWliNHjpw3pr29fcKY0dHRSd2bJE899VRWrVr1ss/v6+tLX19fkmTb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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11af41be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Direct_PPC_Control\n",
      "24.6144284174\n"
     ]
    },
    {
     "data": {
      "image/png": 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Q1d0PdbltV99j+3JMeobP/sqm/pVN/SuX2lc29T8wdXVNpMLH2QAAAABAiAQA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\nPSx6wbJly3LWWWclSc466yz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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11aea51d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "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": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}