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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 3,  8, 10])"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pgmpy.factors.continuous import LinearGaussianCPD\n",
    "import numpy as np\n",
    "\n",
    "mu = np.array([2, 3, 8, 10])\n",
    "sigma = np.array([[2.3, 0, 0, 0], [0, 1.5, 0, 0], [0, 0, 1.7, 0], [0, 0, 0, 2]])\n",
    "\n",
    "cpd = LinearGaussianCPD(\"Y\", mu, sigma, [\"U1\", \"U2\", \"U3\"])\n",
    "cpd.variable\n",
    "cpd.evidence\n",
    "cpd.beta_vector"
   ]
  }
 ],
 "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": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}