{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exponential smoothing\n",
    "\n",
    "Let us consider chapter 7 of the excellent treatise on the subject of Exponential Smoothing By Hyndman and Athanasopoulos [1].\n",
    "We will work through all the examples in the chapter as they unfold.\n",
    "\n",
    "[1] [Hyndman, Rob J., and George Athanasopoulos. Forecasting: principles and practice. OTexts, 2014.](https://www.otexts.org/fpp/7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading data\n",
    "\n",
    "First we load some data. We have included the R data in the notebook for expedience."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:15.020317Z",
     "start_time": "2017-12-07T12:39:14.263100Z"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from statsmodels.tsa.api import ExponentialSmoothing, SimpleExpSmoothing, Holt\n",
    "%matplotlib inline\n",
    "\n",
    "data = [446.6565,  454.4733,  455.663 ,  423.6322,  456.2713,  440.5881, 425.3325,  485.1494,  506.0482,  526.792 ,  514.2689,  494.211 ]\n",
    "index= pd.date_range(start='1996', end='2008', freq='A')\n",
    "oildata = pd.Series(data, index)\n",
    "\n",
    "data = [17.5534,  21.86  ,  23.8866,  26.9293,  26.8885,  28.8314, 30.0751,  30.9535,  30.1857,  31.5797,  32.5776,  33.4774, 39.0216,  41.3864,  41.5966]\n",
    "index= pd.date_range(start='1990', end='2005', freq='A')\n",
    "air = pd.Series(data, index)\n",
    "\n",
    "data = [263.9177,  268.3072,  260.6626,  266.6394,  277.5158,  283.834 , 290.309 ,  292.4742,  300.8307,  309.2867,  318.3311,  329.3724, 338.884 ,  339.2441,  328.6006,  314.2554,  314.4597,  321.4138, 329.7893,  346.3852,  352.2979,  348.3705,  417.5629,  417.1236, 417.7495,  412.2339,  411.9468,  394.6971,  401.4993,  408.2705, 414.2428]\n",
    "index= pd.date_range(start='1970', end='2001', freq='A')\n",
    "livestock2 = pd.Series(data, index)\n",
    "\n",
    "data = [407.9979 ,  403.4608,  413.8249,  428.105 ,  445.3387,  452.9942, 455.7402]\n",
    "index= pd.date_range(start='2001', end='2008', freq='A')\n",
    "livestock3 = pd.Series(data, index)\n",
    "\n",
    "data = [41.7275,  24.0418,  32.3281,  37.3287,  46.2132,  29.3463, 36.4829,  42.9777,  48.9015,  31.1802,  37.7179,  40.4202, 51.2069,  31.8872,  40.9783,  43.7725,  55.5586,  33.8509, 42.0764,  45.6423,  59.7668,  35.1919,  44.3197,  47.9137]\n",
    "index= pd.date_range(start='2005', end='2010-Q4', freq='QS-OCT')\n",
    "aust = pd.Series(data, index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple Exponential Smoothing\n",
    "Lets use Simple Exponential Smoothing to forecast the below oil data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:15.189907Z",
     "start_time": "2017-12-07T12:39:15.022229Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Figure 7.1: Oil production in Saudi Arabia from 1996 to 2007.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=oildata.plot()\n",
    "ax.set_xlabel(\"Year\")\n",
    "ax.set_ylabel(\"Oil (millions of tonnes)\")\n",
    "print(\"Figure 7.1: Oil production in Saudi Arabia from 1996 to 2007.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we run three variants of simple exponential smoothing:\n",
    "1. In ```fit1``` we do not use the auto optimization but instead choose to explicitly provide the model with the $\\alpha=0.2$ parameter\n",
    "2. In ```fit2``` as above we choose an $\\alpha=0.6$\n",
    "3. In ```fit3``` we allow statsmodels to automatically find an optimized $\\alpha$ value for us. This is the recommended approach."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:15.785068Z",
     "start_time": "2017-12-07T12:39:15.191930Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f94b0ca3970>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fit1 = SimpleExpSmoothing(oildata, initialization_method=\"heuristic\").fit(smoothing_level=0.2,optimized=False)\n",
    "fcast1 = fit1.forecast(3).rename(r'$\\alpha=0.2$')\n",
    "fit2 = SimpleExpSmoothing(oildata, initialization_method=\"heuristic\").fit(smoothing_level=0.6,optimized=False)\n",
    "fcast2 = fit2.forecast(3).rename(r'$\\alpha=0.6$')\n",
    "fit3 = SimpleExpSmoothing(oildata, initialization_method=\"estimated\").fit()\n",
    "fcast3 = fit3.forecast(3).rename(r'$\\alpha=%s$'%fit3.model.params['smoothing_level'])\n",
    "\n",
    "plt.figure(figsize=(12, 8))\n",
    "plt.plot(oildata, marker='o', color='black')\n",
    "plt.plot(fit1.fittedvalues, marker='o', color='blue')\n",
    "line1, = plt.plot(fcast1, marker='o', color='blue')\n",
    "plt.plot(fit2.fittedvalues, marker='o', color='red')\n",
    "line2, = plt.plot(fcast2, marker='o', color='red')\n",
    "plt.plot(fit3.fittedvalues, marker='o', color='green')\n",
    "line3, = plt.plot(fcast3, marker='o', color='green')\n",
    "plt.legend([line1, line2, line3], [fcast1.name, fcast2.name, fcast3.name])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Holt's Method\n",
    "\n",
    "Lets take a look at another example.\n",
    "This time we use air pollution data and the Holt's Method.\n",
    "We will fit three examples again.\n",
    "1. In ```fit1``` we again choose not to use the optimizer and provide explicit values for $\\alpha=0.8$ and $\\beta=0.2$\n",
    "2. In ```fit2``` we do the same as in ```fit1``` but choose to use an exponential model rather than a Holt's additive model.\n",
    "3. In ```fit3``` we used a damped versions of the Holt's additive model but allow the dampening parameter $\\phi$ to be optimized while fixing the values for $\\alpha=0.8$ and $\\beta=0.2$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:16.114361Z",
     "start_time": "2017-12-07T12:39:15.786542Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f94b093fdf0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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77yX3jJ6KYdUDJw1PT09z27Zt9xw7cOAApUqVSrI52ELGjBljV0Ql5UqNf7dERERSlEuXoEUL8Pe3Nq7o1i25Z5RghmH4m6bpef/x1LXyKyIiIiJJ49QpaNIEjh6F2bOhTZvknpFNKPw+Aa36ioiISJp26JAVfIODYdkyeMRzTKmJwq+IiIiI3LFjB9x+dsfPz9rEIg1JXd0eRERERCTxrF0L9eqBszOsX5/mgi8o/IqIiIgIwIIF1orvc89Zwbd48eSeUaJQ+BURERF51v3+O7RrB+XKwbp1ULBgcs8o0Sj83jJnzhwMw+DgwYPxfqZevXrc36oN4LfffuOtt94C4Oeff+b333+PPX769OnYz/Xo0YP9+/fbdN5+fn60atXKptd8UvH9fL777jtCQ0MTbdyMGTMm2rVFRETSvO++s1qY1asHK1dCzpzJPaNElerCr+8eX9y/c8duiB3u37nju8c2O4lNmzaNWrVq8ddffz3VdXr16sWrr74KPBh+J06cSOnSpZ/q+qnRw8JvdHR0Es9GREREADBNGDjQ2rSifXtYtAgyZUruWSW6VBV+fff44r3Am8CQQExMAkMC8V7g/dQB+Pr16/z777/8+uuv94TfsLAwXnzxRcqXL0+XLl0ICwuLfW/y5MkUL16cunXr8u+//8YeHzx4MKNGjWLmzJls27YNLy8vPDw8CAsLi10Z/emnn/joo49iz/ntt9/o27cvAH/88QdVq1bFw8ODN998M85wuHTpUkqWLEmtWrWYPXt27PEtW7ZQo0YNKlasSI0aNfjvv/9ir//CCy/QunVrChUqxNixYxk9ejQVK1akWrVqBAcHA9bK7bvvvkuNGjUoW7YsW7ZsAeDGjRu88cYbVKlShYoVKzJv3rxH/nxu++GHHzh9+jT169enfv36gLVS+/nnn/P888+zcePGeO85Y8aMDBgwgAoVKlCtWjXOnTsHwPHjx6levTpVqlRh4MCBCf7fWURERG6JjoY+feCLL6B7d5gxA9KlS+5ZJYkUFX7fXfou9X6rF++r+7zuhEbeu4IYGhlK93nd4z3n3aXvPnLcuXPn0qxZM4oXL0727NnZvn07AD/99BMuLi7s3r2bAQMG4O/vD8CZM2cYNGgQ//77LytWrIizlKFjx454enri6+vLzp07cXZ2vue9u0Pr9OnT6dKlCwcOHGD69On8+++/7Ny5E3t7e3x97w32N2/epGfPnixYsIB169Zx9uzZ2PdKlizJ2rVr2bFjB0OHDuXTTz+NfW/v3r38+eefbNmyhQEDBuDi4sKOHTuoXr16bJkGWEF3w4YNjB8/njfeeAOA4cOH06BBA7Zu3crq1av58MMPuXHjRrw/n7u9/fbbPPfcc6xevTp2O+YbN25QtmxZNm/eTI4cOeK95xs3blCtWjV27dpFnTp1mDBhAgDvvPMO//vf/9i6dSt58+Z95P++IiIicpeICPDygp9+go8+ggkTwN4+uWeVZFJU+H2U8OjwxzqeUNOmTePFF18E4MUXX2TatGkArF27lq5duwJQvnx5ypcvD8DmzZupV68euXLlwsnJiS5dujzWeLly5aJw4cJs2rSJS5cu8d9//1GzZk1WrlyJv78/VapUwcPDg5UrV3Ls2LF7zj148CCFChWiWLFiGIYROz+AkJAQOnXqRNmyZXnvvffYt29f7Hv169cnU6ZM5MqViyxZstC6dWsAypUrR0BAQOznXnrpJQDq1KnD1atXuXLlCsuXL+err77Cw8ODevXqcfPmTYKCguL9+TyKvb09HTp0AHjoPTs5OcXWM1euXDl2nv/++2/sPF955ZUEjSkiIiLAjRvWTm3Tp8PIkdbLMJJ7VkkqRW1y8V2z7x76vvt37gSGBD5w3C2LG36v+T3RmJcuXWLVqlXs3bsXwzCIjo7GMAy+/vprAIx4/kLEdzyhunTpwowZMyhZsiTt2rXDMAxM06Rbt26MGDHioefGN/bAgQOpX78+c+bMISAggHr16sW+l+6uX2XY2dnFfm9nZ0dUVFS81749r1mzZlGiRIkEz+Vh0qdPj/2tf2E+7J4dHR1jr29vb//QeYqIiMgjBAdDq1aweTNMnGiVOzyDUtXK7/CGw3FxdLnnmIujC8MbDn/ia86cOZNXX32VwMBAAgICOHHiBIUKFWL9+vXUqVMn9lfwe/fuZffu3QA8//zz+Pn5cenSJSIjI/n777/jvHamTJm4du1anO+1b9+euXPnMm3atNiV44YNGzJz5kzOnz8PQHBwMIGB94b9kiVLcvz4cY4ePQoQu0oN1spv/vz5AavO90lMnz4dgPXr15MlSxayZMlC06ZN+fHHHzFNE4AdO3YAxPvzud/Dfg4Juef71axZM7Y2+/6yEBEREYnD6dPWFsX+/vD3389s8IVUFn69ynnh09oHtyxuGBi4ZXHDp7UPXuW8nvia06ZNo127dvcc69ChA3/++Sf/+9//uH79OuXLl+frr7+matWqAOTLl4/BgwdTvXp1GjVqRKV4dj957bXX6NWrV+wDb3fLli0bpUuXJjAwMPa6pUuX5osvvqBJkyaUL1+exo0bc+bMmXvOS58+PT4+PrRs2ZJatWrh5uYW+95HH33EJ598Qs2aNZ+4i0K2bNmoUaMGvXr14tdffwWsFeXIyEjKly9P2bJlYx8yi+/ncz9vb2+aN28e+8Db3RJyz/f7/vvvGTduHFWqVCEkJOSJ7lNERCRN8/UFd3ews4P8+aFCBQgIgMWLrc4OzzDj9mpeUvD09DTv7wN74MABSpUqlWRzkPjVq1ePUaNG4enpmdxTsQn93RIRkWeSry94e8P9bUaHDrVamz0jDMPwN03zgVCTqlZ+RUREROQRBgx4MPgC3PqN7rMuRT3wJsnLz88vuacgIiIiTyso6PGOP2O08isiIiKSVpgmZMkS93uurkk7lxQqRYTfpKw7lmeD/k6JiMgzJzoa3n4brlx5cNMKFxcY/uTdsdKSZA+/6dOn59KlSworYjOmaXLp0iXSp0+f3FMRERFJGqGhVheHsWOhXz/47Tdwc7M2sHBzAx8fa1c3Sf6a3wIFCnDy5EkuXLiQ3FORNCR9+vQUKFAguachIiKS+M6fh9atYetW+OEH6NvXOn7XLrByR7KHX0dHRwoVKpTc0xARERFJff77D5o3h7NnYc4caNs2uWeU4iV7+BURERGRJ7B+vRV27e1h9Wp4/vnknlGqkOw1vyIiIiLymP7+Gxo1ghw5YONGBd/HoPArIiIiklqYJnz7LXTuDJUrW8G3SJHknlWqovArIiIikhrcbmX2wQfQsSP884+18iuPReFXREREJKW7v5XZ9Ong7Jzcs4qXry+4u4OdnfXV1ze5Z3SHHngTERERScnia2WWQvn6gre3ldcBAgOt7yFltBrWyq+IiIhISvXff1CtGuzZY7UyS+HBF2DAgDvB97bQUOt4SqCVXxEREZGUKBW2MgsPt1Z64xIUlLRziY9WfkVERERSmlTWysw0Yf58KFMm/s+4uibdfB4mQeHXMIwAwzD2GIax0zCMbbeOZTcMY4VhGIdvfc2WuFMVERERSeNSYSuz/fuhWTNrkdrJCfr3BxeXez/j4gLDhyfP/O73OCu/9U3T9DBN0/PW9x8DK03TLAasvPW9iIiIiDyJVNbK7PJlePddKF8eNm+G776DXbvgq6/Axwfc3MAwrK8+PinjYTd4uprftkC9W3+eAvgB/Z9yPiIiIiLPntBQeOklq3agXz/4+murT1gKFB0NEyfCZ5/BpUtWJ4dhwyBXrjuf8fJKOWH3fgn9qZrAcsMw/A3DuNWsgjymaZ4BuPU1d2JMUERERCRNO38e6teHBQusVmajRqXY4Lt2rVWN0asXlCoF27fDzz/fG3xTuoSu/NY0TfO0YRi5gRWGYRxM6AC3wrI3gGtKqXQWERERSQn++w+aN4ezZ61WZm3bJveM4hQYCB99BDNmQMGC1h4bnTpZZQ2pTYL+WWGa5ulbX88Dc4CqwDnDMPIB3Pp6Pp5zfUzT9DRN0zNXavpngYiIiEhiWr8eatSA69etVmYpMPiGhsLgwVCypFWRMWgQHDxoPY+XGoMvJCD8GoaRwTCMTLf/DDQB9gLzgW63PtYNmJdYkxQRERFJU1J4KzPTtFZ3S5aEIUOgTRtrkXrw4Ac7OaQ2CVn5zQOsNwxjF7AFWGSa5lLgK6CxYRiHgca3vhcRERGR+KSCVmY7dkDduvDii5A9O6xZYwXhtFK9+siaX9M0jwEV4jh+CWiYGJMSERERSXOio63eYGPHWq3Mfv8dnJ2Te1axLlywOjhMmGCF3p9/hh49rA3m0pKU+SihiIiISFoSGgrt21vBt18/ayk1hQTfyEirR2+xYvDrr1ar4cOH4c03017wBYVfEREREdvz9QV3d6tlWcGCUK5cimxltnw5VKgA771nlR3v3m0F4WxpeN/ep9nkQkRERETu5+tr7fwQGmp9f/Kk9fW996Bv3+Sb112OHIH337fyeJEiMG8etG6dejs4PI6U8c8OERERkbRiwIA7wfdus2cn/Vzuc+0a9O8PpUtb3dW++gr27bO6OTwLwRcUfkVERERsKyjo8Y4ngrurLtzd4Y8/YMoUKF7c2jn55Zfh0CErCKdLl2TTShFU9iAiIiJiK9HRkCkTXL364HtJ1Cvs/qqLwEDo1g1iYqBqVZg7N8W1FU5SCr8iIiIitnDtGnh5WcHXwQGiou685+ICw4cnyTTiqrqIibmzn0YKedYu2Tzjty8iIiJiAwEBULMmLF5stTP77Tdwc7MKad3cwMfHCsZJIL7qiuBgBV/Qyq+IiIjI0/n3X2jXDiIiYMkSaNzYOp5EYfc207S6Ntjb37vofFta2aHtaSn/i4iIiDypKVOgQQPImhU2b74TfJPY3r3W0O3aQe7cDz7EloRVFymewq+IiIjI44qOho8+gtdeg9q1YdMmKFEiyacRHGy1DvbwAH9/aw+NwEBrp7ZkqrpI8VT2ICIiIvI4bj/YtmAB/O9/8P334OiYpFOIioJffoHPP4crV6BXLxgyBHLmtN738lLYjY/Cr4iIiEhCBQRYW6EdOGA92NanT5JPYeVKeOcda3OK+vWt7F2uXJJPI9VS2YOIiIhIQqxfbzXKPXnSerAtiYPvsWPQvj00agQ3bsCsWVYQVvB9PAq/IiIiIo/y2293HmzbtClJH2y7fh0+/RRKlYLly60H1w4csILws7IlsS0p/IqIiIjE5/aDba+/DnXqWB0dkujBtpgYmDrV2pJ4xAjo0gX++88KwunTJ8kU0iTV/IqIiIjE5do1ePllWLgQeveG775LsgfbNm+26no3b4YqVawSh+rVk2ToNE8rvyIiIiL3CwiAGjWs2t5x46xXEgTfM2es7mnVqlkty377zaqyUPC1Ha38ioiIiNxt/Xprt4ioKFi61HrCLJHdvGktLA8fbm0U9/HHVnlDpkyJPvQzRyu/IiIiIrfdfrAte3ar5iCRg+/tLYnLlIFPPoGGDWH/fqvGV8E3cSj8ioiIiERHw4cfWg+21a1r1RoUL56oQ+7bB02awAsvWA+wLV8Oc+dCkSKJOuwzT+FXREREnm1Xr1oJdNQoq3fv4sWQLVuiDXd7S+IKFWDbNmtL4l27krR72jNNNb8iIiLy7Dp+3Nqx7eBB66G23r0TbaioKPDxgYED496SWJKGVn5FRETk2bRunbVj26lT1oNtNgy+vr7g7g52dtbXTz+FihWtheUKFWDnTitrK/gmPa38ioiIyLNn8mR4800oVAgWLLBpfa+vL3h7Q2io9X1goPUAW86cMHu2VWGhndmSj1Z+RURE5NkRHQ0ffABvvJFoD7YNGHAn+N7N2dnqoKbgm7y08isiIiLPhqtXrR3bFi2Ct96CMWPAwbZRyDStld64nDxp06HkCWnlV0RERNK+Y8esHduWLoXx4+HHH20efLduhZo143/f1dWmw8kTUvgVERGRtOfuJ87y5rWeMjt9GpYtg//9z6ZDnT1rVVFUrWplbG9vcHG59zMuLtbubZL8FH5FREQkbbn9xFlgoFWHcO4c3LhhFeM2bGizYSIi4JtvrJLhP/6Ajz6CQ4fgl1+slmZublZ9r5ub9b2Xl82GlqdgmKaZZIN5enqa27ZtS7LxRERE5Bnk7h534a2bGwQEPPXlTdMqG37/fTh8GFq1gtGjoVixp7602JBhGP6maXref1wrvyIiIpK2BAU93vHHcPAgtGhh7Ythbw9Lllid0hR8Uw+FXxEREUk7tmyx6nzj8hRPnF25Yq30lisHGzdajSJ274ZmzZ74kpJMFH5FREQkbfj1V6hdG7JmhfTp733vCZ84i46GCROsut7vvoPXX7fqet99FxwdbTFpSWoKvyIiIpK6hYdDr17Qo4e1ccV//8HEiU/9xNn69VClivXsXIkS4O9vXSZ37kS6jzTEd48v7t+5YzfEDvfv3PHd45vcU4qlTS5EREQk9Tp5Ejp2hM2b4eOP4YsvrGJcL68nbq9w4oTVueGvv6BgQetr587amS2hfPf44r3Am9BIa5u7wJBAvBd4A+BVLvlbXmjlV0RERFKnNWugcmXYtw9mzoQRI6zg+4TCwmDoUGuVd+5c+Pxz6wG3Ll0UfB/HJ/98Eht8bwuNDGXAygHJNKN7aeVXREREUhfThB9+gH79oGhR8PODUqWe6nKzZsEHH1gd0jp1svr3urnZbspplWmaHAk+wqaTm6zXqU2cuHoizs8GhTx9tw1bUPgVERGR1CM0FHr2hD//hLZt4fffIXPmJ77c7t3wzjtWfq5QAaZMscqGJW5Xbl5hy6ktsWF386nNBIcFA5DJKRNV81clc7rMXA2/+sC5rllSxv7OCr8iIiKSOhw7Bu3awZ49Vm3vJ5/E39bsES5ehIEDrQfYsmWDn36yMvVTVE2kOdEx0ey7sO/Oqu7JTRy4eAAAA4MyucvQrmQ7qhWoRrUC1SiVsxT2dvYP1PwCuDi6MLxhytjfWeFXREREUr6lS+Hll60/L178xA12IyPh55+tet5r1+Ctt2DwYCsAP+vOXT/H5lObY4Pu1tNbuR5xHYCcLjmpVqAaXuW8qFagGlXyVyFzurhX3G8/1DZg5QCCQoJwzeLK8IbDU8TDbqDtjUVERCQli4mxHmQbOBDKl4fZs6Fw4Se61D//WCUO+/dDo0ZW394yZWw73ZTCd4/vQ8NnRHQEO8/uvGdV9/iV4wA42DngkdeDavmrxa7qFs5WGCOVPfUX3/bGWvkVERGRlCkkBLp1g3nzrFXfCROszSoSwNcXBgywdjTOlw/y5oXt263cPHcutGmTdjs4xNVqrOf8nmw6uQlHO0c2ndzE9jPbCY8OB6BA5gJUK1CNPlX6UK1ANSrlq4Szo3Ny3kKi0sqviIiIpDz791v1vUePwrffwttvJzit+vpaG1OE3ttti86drefj0qVLhPmmIG7fucXbWSG9Q3o8n/OMXdV9vsDzFMhcIIlnmDS08isiIiKpw6xZ8Npr1irvypWP3X7h008fDL5g7YORFoNvVEwU289sZ03AGvwC/eINvgYGVz++iqP9s70vc4LDr2EY9sA24JRpmq0MwxgM9AQu3PrIp6ZpLrb9FEVEROSZEB1t1SqMHAnPP29tXFHg8VYlt261Sh3iEt/x1CYyOpLtZ7bjF+DHmsA1rA9az7WIawCUzFmSjE4ZYx9Uu5trFtdnPvjC4638vgMcAO5+tG+MaZqjbDslEREReeZcugQvvQQrVsCbb8L33z/WMu3Zs1bns99+s7qfxcQ8+BnXlNFm9rFFRkey7fQ21gSuwS/Aj/VB67kReQOAUjlL0bV8V+q516OOWx3yZsyb4luNJbcEhV/DMAoALYHhwPuJOiMRERF5tmzfDu3bw5kzMHEidO+e4FPDw63N3oYNg5s34aOPoFgxq6vD3aUPLi4wPJVkv4joCLae2hobdjec2BAbdsvkKsNrHq9R160uddzqkCdjngfOT+mtxpJbQld+vwM+AjLdd/wtwzBexSqH6Gea5mUbzk1ERETSut9/t1Z6c+aE9euhSpUEnWaasGgRvPceHDkCrVtbz8UVK2a97+x8p9uDq6sVfL1SaPYLjwpn6+mtsWUM/wb9S1hUGADlcpfjdY/XY1d2c2XIlaBrepXzUtiNxyO7PRiG0QpoYZpmb8Mw6gEf3Kr5zQNcBExgGJDPNM034jjfG/AGcHV1rRwYGGjbOxAREZHUJyIC3n8fxo2DevVg+nTInTtBpx48CO++C8uWQcmSVr/epk0Tc7KP72F9dsOjwtl8anPsA2obT2yMDbvl85Snnls96rnXo7ZbbXK65EzO20jV4uv2kJDwOwJ4BYgC0mPV/M42TbPrXZ9xBxaapln2YddSqzMRERHhzBno1An+/Rf69YOvvgKHR/8y+soVGDoUfvwRMmSwdmbr0wccU9gzXHHV3KazT0fLYi0JvhnMppObuBl1EwODCnkrUM+tHnXd61LbtTY5XHIk48zTlicOv/ddpB53Vn7zmaZ55tbx94DnTdN88WHnK/yKiIg84zZsgI4drQ0sfv0VXnxodACsJhCTJlllDBcvQs+e8MUXkCthFQBJ7mF9divlq0Rdt7rWyq5rbbI5a1/lxJIYfX6/NgzDA6vsIQB48ymuJSIiImmZacJPP1n1Cq6uVs1CuXKPPG3dOuvhtR07oHZtqwlExYqJP93HdeHGBZYdXcbSI0sf2mfX39s/iWcm93us8Guaph/gd+vPryTCfERERCQtuHt/4QIFwN3dSrItWljvZc360NNPnLA6N/z1FxQsaH3t3DnlbEkcHRPNllNbWHJkCUuPLGXb6W2YmORyyUUGxwyx3Rnu5pollfZaS2O0w5uIiIjY1v37C584Yb3at4e//7Ya8cYjLAy++cYqAzZNGDTICsEuLkk094c4e/0sy44sY8mRJSw/upzLNy9jZ9jxfP7nGVJvCM2LNadSvkpM2ztNfXZTMIVfERERsa0BA+LeX9jfP97ga5rWhm4ffGAtFnfuDF9/DW5uiTzXh4iKiWLjiY0sPbKUJUeWsOPsDgDyZMhDmxJtaF60OY2LNCa7c/Z7zlOf3ZTtsR54e1p64E1EROQZYGdnpdn7GUacW6/t3g1vvw1r1kCFClZdb926STDPOJy6eoqlR5ay9OhSVhxdQUh4CPaGPTUK1qBZ0WY0L9qcCnkrYGfEv3otKUNiPPAmIiIi8iBXV4irr/99+wtfvAgDB4KPD2TLBj//DD16gL19Es0Taze1DSc2sOTwEpYeXcruc7sByJ8pPx1Ld6R50eY0LNyQrOmzJt2kJFEp/IqIiIhtDR9+b80v3LO/cGSkFXQ//xyuXYO33rJ69mazYdevh20yERQSFFvKsPLYSq5FXMPBzoFarrUY2WgkzYs2p2zushgp5ek6sSmVPYiIiIjt3d3t4a79hf/5x2pdtn8/NGpk7c5WpoyNh45nk4mGhRoSEBLA/gv7ASiYuSDNizanebHmNCzUkEzpMtl2IpKsVPYgIiIiScYXLwbgRRDgCrxzHta8APPmQeHCMHcutGmTOK3LBqwccE/wBQiPDmfxkcU0KtyI7hW706xoM0rlLKXV3WeQwq+IiEhaNWwY5M1rbYmWhO7vdBYYCO+/D05OMGIEvPcepEtn+3FPhJxg9oHZBIbEUW+MtcnEildW2H5gSVUUfkVERNIiHx+rqPaNN6ynyJJwhTO+Tme5csHHH9t2rCPBR5i1fxazDsxi6+mtADjaORIZE/nAZ7XJhIDCr4iISNozbx7873/QsiX88kuSb4sWFPfuvpw+/fTXNk2TfRf2MWv/LGYfnB3bncHzOU9GNBxB+1Lt2Xp6qzaZkHgp/IqIiKQlGzbAiy+CpydMnw4OSf+f+gR2Oksw0zTxP+PP7AOzmXVgFocuHcLAoKZrTcY0HUO7ku1wy3pnN4ziOYoD2mRC4qZuDyIiImnFgQNQs6ZVX/Dvv5AzZ7JM4/6aX7A6nfn4gFcC82eMGcOGExuYfWB2bB2vvWFP/UL1aV+yPS+UfIF8mfIlzg1ImqBuDyIiImnZqVPQtKn1JNnSpckWfOFOwI2j09lDRcVEsSZgDbMOzGLOwTmcvX4WJ3snmhRpwqC6g2hTog05XHIk/g1ImqbwKyIiktpduQLNm1tf166FQoWSe0Z4eSVslTc8Kpx/jv3DrAOzmPffPILDgnFxdKF50eZ0KNWBlsVbkjld5sSfsDwzFH5FRERSs5s34YUX4OBBWLIEPDxi31q92loALlcu2WYXpxsRN1h6ZCmzDsxi4aGFXIu4RuZ0mWldvDUdSnWgadGmuDi6JPc0JY1S+BUREUmtoqPhlVdgzRqYNg0aNox9a9MmaN0aKlcGP78kb/jwwPbCn9X+DGdHZ2YfnM2Sw0sIiwojh3MOOpfpTIdSHWhYuCFO9k5JO0l5Jin8ioiIpEamCe++CzNnwujRVoeHW/bssaog8uSBv/5KnuB7d6uxwJBAei60NtrIlzEfb1R8gw6lOlDbrTYOdooikrT0N05ERCQ1GjkSxo6FDz6wtky75cgRaNLE6q7wzz+QLxkaIsS1vTBAngx5OPn+SewMu6SflMgtCr8iIiKpzW+/wSefWE+UjRwZe/jkSWjUCCIjk/e5t6CQuHe5OH/jvIKvJDv9DRQREUlNliyxtitu3BgmTQI76z/lFy9aK77BwVans9Klk2+K8W0jrO2FJSVQ+BUREUkttmyBjh2hQgWYNQucrAfErl6FZs3g+HFYsMDa3C05DW84/IFuDdpeWFIKhV8REZHU4PBhaNkS8uaFxYshUyYAwsKsrg67dsHff0Pdusk8T8CrnBc+rX1wy+KGgYFbFjd8Wvtoe2FJEVTzKyIiktKdPWvt3gZWTUOePIBV29upE6xbZ20p3KrVvacN9htM3ox56eXZK4knbAVghV1JibTyKyIikpJduwYtWsC5c9aKb7FigNXi99VXYdEiGD8eXnrp3tO+XPclQ9YMYdvpbZimmQwTF0mZtPIrIiKSUkVEQPv2VuPeBQugShXAavHbp4/Vw/err6DXfQu7ozeOZsCqAXQt35VfWv2CkdSNfkVSMIVfERGRlCgmBl5/3WrW+9tv1hNtt3zyCfzyC/Tvb73uNm7LOPot70en0p2Y3HYy9nb2STtvkRROZQ8iIiIpUf/+8OefMGIEdOsWe/irr6zWvm++ab11t4nbJ/LWkrdoW6Itvu19tXuaSBwUfkVERFKa0aNh1Cjo2/eepd2ff7ZWfV96CcaNu3fb4qm7puK9wJtmRZsxveN0HO0dk2HiIimfwq+IiEhKMm0a9Otn9fMdMyY24U6bBr17W93OpkwB+7uqGWbsm8Fr816jfqH6zO48m3QO6fD19cXd3R07Ozvc3d3x9fVNphsSSVn0+xAREZGUYuVKq8Shbl2YOjU24S5caHV2qF3b6uXreNei7tyDc3l51svUKFiD+S/Ox9nRGV9fX7y9vQkNDQUgMDAQb29vALy81H5Mnm1a+RUREUkEj73yumMHtGsHJUvC3LmQPj0Afn5WL98KFayGD3Z24Zw5c4Z9+/bx9Zyv6TSjE26ObjQPbs6IoSPo3bv3PcH3ttDQUAYMGJA4NyuSihhJ2fvP09PT3LZtW5KNJyIikhzuX3kFcHFxwcfHBy8vL0zT5MaNGwQHBxMcHEzovn1U6tOHSHt7fn/zTYKiowkODubo0WysXTsYB4czZM/ejpCQo3euWRh4GTgP/A7cBDs7O7Jnz87FixfjnJdhGMTExCTy3YukDIZh+Jum+cBm3wq/IiIiNubu7k5gYOADxx0cHMiRIwfBwcFERkYCkBP499bXmsBBwMnJicyZq3H58lwcHG5St+4A8ueH7Nmzkz17di5lvMTYK2PJ75yfibUnUihPIbJnz06mTJliV5rjGt/NzY2AgIBEvHORlCO+8KuaXxERERsLCgqK83hUVBRt27aNDbG5M2Sg9XffkSUwkICJE1lRvz7Zs2fn7Flnatc2yJXL2rq4aNFJsdfYeGIjTf5oQuEchVnz2hpyZ8j9wDjDhw+Pc+V5+PDhtr9ZkVRG4VdERMSGdu3ahb29PVFRUQ+85+bmxi+//GJ9ExkJL7wAR4/CnDkUadMGgDNnoHFjCAuDNWugaNE75287vY1mvs3ImzEvK19dGWfwhTsPtQ0YMICgoCBcXV0ZPny4HnYTQeFXRETEZv7880969OhBxowZuXnzJjdv3ox9756VV9MEb29YvNjaqu1W8A0OhiZN4Nw5a2O3cuXuXHvX2V00mdqE7M7ZWfXqKp7L9NxD5+Ll5aWwKxIHdXsQERF5SpGRkbz77rt4eXlRpUoVDh48yMSJE3Fzc8MwDNzc3GIfdgNg4EBry+LBg60QDFy7Bs2bw6FDMG8eVKt25/r7L+yn0dRGZHDKwKpXV1EwS8Ekv0eRtEIPvImIiDyFc+fO0blzZ9auXcu7777L119/jaPjQ3ZXGzcO3noLeva0Vn0Ng5s3rc0r1qyBmTOtaojbDl06RN3f6gKw9rW1FMtRLHFvSCSN0ANvIiIiNrZp0yY6dOjA5cuX+eOPPx5dZjBrlrVlcZs2MH48GAZRUfDii7BqlbVz293B99jlYzSY0oDomGj8XvNT8BWxAZU9iIiIPCbTNPnll1+oU6cO6dOnZ+PGjY8OvmvXgpcXVK9u7VXs4EBMDLzxhlXm8MMP1i5utwWFBNHw94aERYXxz6v/UDpX6cS9KZFnhMKviIjIY7h58yY9e/akV69eNGrUiG3btlGhQoWHn7Rnj7XaW6iQtU2biwumCe+8Y+1iPGyYtSB82+lrp2n4e0OCw4JZ3nU55fOUT9ybEnmGKPyKiIgkUFBQELVr1+bXX39l4MCBLFiwgGzZsj38pBMnrCfZMmSApUshe3YABg2CsWPh/ffh7l2Hz10/R8PfG3L2+lmWei2l8nOVE/GORJ49qvkVERFJgFWrVtGlSxciIiKYN28ebW61J3uo4GBo2hSuX7d2q3BzA+Dbb63V3u7dYdQoMAzr4xdDL9JoaiOCQoJY4rWE6gWrJ+IdiTybtPIrIiLyEKZpMmrUKBo3bkzu3LnZsmVLwoKvaUKHDtYmFnPnxjbt/fVX+OAD6NQpttkDAFduXqHJ1CYcvnSY+S/Op45bncS7KZFnWILDr2EY9oZh7DAMY+Gt77MbhrHCMIzDt74+4vc+IiIiqcv169d58cUX+fDDD2nfvj2bNm2iRIkSCTt51izw84Mff4R69QD4+2+rrW/TpvDHH2Bvb330avhVmv3RjL3n9zKnyxwaFm6YKPcjIo+38vsOcOCu7z8GVpqmWQxYeet7ERGRNOHw4cNUq1aNmTNn8vXXXzNjxgwyZcqUsJMjI+HTT6FMGau2Aavc93azh1mzwMnJ+uiNiBu0/LMl/mf8+bvT3zQv1jyR7khEIIHh1zCMAkBLYOJdh9sCU279eQrwgk1nJiIikkwWLFiAp6cnZ8+eZdmyZXz44YcYt+sTEmLiRDh8GL76CuztWb8e2re3svDChdazbwBhkWG0+asNG05swLe9L21Ltk2cGxKRWAld+f0O+AiIuetYHtM0zwDc+prbtlMTERFJWjExMQwaNIg2bdpQtGhR/P39adSo0eNd5Pp1GDIEateGli3ZscPava1gQVi2DLJmtT4WHhVOu+ntWH18NVNemELnMp1tfj8i8qBHdnswDKMVcN40TX/DMOo97gCGYXgD3gCurq6Pe7qIiEiSuHz5Ml27dmXx4sW89tprjB8/Hmdn58e/0JgxcO4czJ3Lf4cMmjaFLFlgxQrIfWuZKCI6gk5/d2LZ0WVMbD2RruW72vZmRCReCWl1VhNoYxhGCyA9kNkwjD+Ac4Zh5DNN84xhGPmA83GdbJqmD+AD4Onpadpo3iIiIjazZ88e2rVrR1BQED/99BNvvvnm45U53Hb+PHz9NbRvT1iFarQoax3+5x+4vf4TFROF12wvFhxawLgW4+heqbvtbkREHumRZQ+maX5immYB0zTdgReBVaZpdgXmA91ufawbMC/RZikiIpJI/vrrL6pVq0ZYWBhr1qyhV69eTxZ8Ab74AsLC4Msv+f57OHbM2sm4eHHr7eiYaLrN7cbM/TMZ3WQ0vav0tt2NiEiCPE2f36+AxoZhHAYa3/peREQkVYiKiqJfv3689NJLVK5cGX9/f6pXf4pNJY4ehZ9/hh49OJ+tBF9+Ca1bQ8NbXctizBi8F3jz554/+bLBl7xX/T3b3IiIPJbH2uHNNE0/wO/Wny8BakQoIiKpzvnz5+nSpQt+fn68/fbbjBo1CkdHx6e76MCB4OgIgwYxaJC1APzNN9Zbpmny1uK3mLRzEp/X+ZxPan/y9DchIk9E2xuLiMgzZfPmzXTo0IHg4GCmTp1K1642eNjM39+qbxgwgH3B+fDxgd69oUQJK/i+t+w9ftr2Ex/V+IjB9QY//Xgi8sS0vbGIiDwzJkyYQJ06dXB0dGTDhg22Cb4AH38MOXLARx/x4YeQKRMMGmQF309WfsL3m7/nneff4atGXz15PbGI2ITCr4iIpEm+vr64u7tjZ2eHm5sb9evXx9vbm/r16+Pv74+Hh4dtBlqxwmrnMHAgyzZmZskS+OwzyJkThq8bzsh/R9Krci/GNB2j4CuSAhimmXTdxzw9Pc1t27Yl2XgiIvJs8vX1xdvbm9DQ0HuOt23bllmzZmFvb2+bgWJiwNMTLl8met9BPJ5Px40bcOAAHLi8k0q/VOLlci/ze7vfsTO03iSSlAzD8DdN0/P+46r5FRGRNGfAgAEPBF+AnTt32i74Avz1F+zYAX/8wSTfdOzdC3//DU5OJu8ufZfsztn5sfmPCr4iKYjCr4iIpDlBQUGPdfyJhIfDgAHg4cG1Vi/xWXGoWRM6dIC5B+eyJnAN41qMI5tzNtuNKSJPTeFXRETSHFdXVwIDA+M8bjM//wwBAbBsGSO/seP8eZg/HyKiw/lgxQeUzlUa78rethtPRGxCv4cREZE0p2/fvg8cc3FxYfjw4bYZICQEhg2Dhg0JKtGYb7+Fl1+G55+HHzb/wLHLxxjTdAwOdlpjEklpFH5FRCTN2bx5M05OThQoUADDMHBzc8PHxwcvLy/bDDBqFFy6BCNH8ukAA9OEL7+Ec9fPMWztMFoWa0mTIk1sM5aI2JT+SSoiImnKli1b+Pvvvxk0aBCDBw+2/QBnzsDo0fDii2yNqYyvL3zyCbi5wZsLPicsKoxRTUbZflwRsQmFXxERSTNM06R///7kypWLfv36Jc4gQ4ZAZCTmsC94/3XIndva42LX2V1M3DGRvlX7UjJnycQZW0SemsKviIikGUuXLsXPz48ff/yRTJky2X6A//6DiROhd2/m7C7C+vXWc2+ZMpm8P/d9sqbPyud1P7f9uCJiM9rkQkRE0oTo6GgqVqxIaGgo+/fvx8nJyfaDdOgAy5cTvv8oZernJn162LkTFh+dT9u/2vJj8x95q+pbth9XRB6bNrkQEZE07c8//2TPnj389ddfiRN8N22C2bNhyBDG/Z2bo0dhyRKIMSLot7wfpXKW4s3Kb9p+XBGxKYVfERFJ9W7evMlnn31G5cqV6dSpk+0HME346CPIk4dL3d5nmAc0bQrNmsHojWM5EnyExS8vxtHe0fZji4hNKfyKiEiqN378eIKCgpg0aRJ2donQxXPRIli3DsaPZ+jojFy9anU7u3DjAkPXDKVZ0WY0L9bc9uOKiM0p/IqISKp25coVhg8fTpMmTWjYsKHtB4iOtto5FC3KoTo9GP829OgBZctC70WDuB5xnW+bfGv7cUUkUSj8iohIqvb1118THBzMyJEjE2eAqVNh3z6YMYOPBjiSPj0MHQp7z+/lF/9f6O3Zm9K5SifO2CJic9rhTUREUq1Tp07x3Xff4eXlhYeHh+0HCAuDgQOhalX8cnZk3jz49FPIndvkvWXvkTldZgbXG2z7cUUk0WjlV0REUq0hQ4YQFRXFsGHDEmeAsWPh5Elipkzl/X4Grq7w7ruw6PAi/jn2D981/Y4cLjkSZ2wRSRQKvyIikiodOHCAX3/9lb59+1KoUCHbD3D5Mnz5JTRvztQT9dixA3x9wd7Jam1WIkcJelfpbftxRSRRKfyKiEiq9Omnn5IhQwY+++yzxBngq68gJITQQV8xoANUqQIvvgg/bBnPoUuHWPjSQrU2E0mFFH5FRCTV2bBhA3PnzuWLL74gZ86cth/gxAn4/nt45RVGLSvPqVPw118QfPMiQ9YMoUmRJrQo1sL244pIolP4FRGRVMU0Tfr370/evHl59913E2eQQYPANDnXZygj60PHjlCrFry1eDBXw68yusloDMNInLFFJFEp/IqISKqyYMEC1q9fz88//0yGDBlsP8DevTBlCrz3Hp/+4kZkpFUBsf/Cfn7e9jO9KveiTO4yth9XRJKEYZpmkg3m6elpbtu2LcnGExGRtCUqKooKFSoQFRXF3r17cXRMhJrb1q1h3Tr2zD1KhQY5eP99aze35r7N2XhiI0fePkJOl0QotRARmzIMw980Tc/7j2vlV0REUo3ff/+d/fv3M2vWrMQJvmvXwsKFmF+O4N1hOcieHT77DJYcXsLSI0sZ3WS0gq9IKqeVXxERSRXCwsIoVqwYBQoUYOPGjbavuTVNqFEDTpxg8feHadnRmR9+gF69Iyn/c3miY6LZ23svTvZOth1XRBKFVn5FRCRV++GHHzh16hS+vr6J87DZnDmwaRNRv0yk32fOFC8OvXrBz9t+5uDFg8x7cZ6Cr0gaoPArIiIpXnBwMCNGjKBly5bUrVvX9gNERcEnn0CpUvjc7MbBgzBvHlyLCmaQ3yAaFmpI6+KtbT+uiCQ5hV8REUnxRowYwdWrV/nqq68SZ4BJk+DQIa77zuXztx2oX9967u3dpUMICQ9hdFO1NhNJK+ySewIiIiIPExQUxI8//ki3bt0oW7as7Qe4ccPq61uzJkN3tCE4GL79Fg5ePMC4rePoWakn5fOUt/24IpIstPIrIiIp2qBBgwAYMmRI4gzw3Xdw9iynf5jJ910NunWDihWh5Z8fkMEpA0PrD02ccUUkWWjlV0REUqw9e/YwZcoU+vbti6urq+0HuHgRRo6Etm15b2ZNHBzgiy9g6ZGlLD68mIF1BpI7Q27bjysiyUbhV0REUqxPPvmELFmy8MknnyTOAF98ATdusKPzCGbMgI8+gjz5onh/2fsUyVaEvlX7Js64IpJsVPYgIiIp0po1a1i0aBEjR44ke/bsth/g+HEYPx7z9Tf43w+leO45+OAD+GXbLxy4eIA5XeaQziGd7ccVkWSl8CsiIimOaZr079+f/Pnz07dvIq2+DhwIDg7MrzSYzb/C5MkQYXeZz/0+p757fdqWaJs444pIslL4FRGRFGf27Nls3ryZX3/9FWdnZ9sPsGMH+PoS9eEnvPN1fjw84NVXod/yoVwOu8yYpmPU2kwkjVL4FRGRFCUyMpJPP/2UMmXK0K1bt8QZ5OOPIXt2xrp8RGCg1eb3yOVDjN06lh6VelAhb4XEGVdEkp3Cr4iIpCiTJk3i0KFDzJ8/H3t7e9sP8M8/sHw514Z8y+ejstKmDTRoAG2mfYCzgzPD6g+z/ZgikmIo/IqISIpx48YNBg8eTK1atWjVqpXtB4iJsVZ93dz49GQfwsLg669hxdEVLDi0gJGNRpInYx7bjysiKYbCr4iIpBhjxozh7NmzzJo1K3FqbmfMAH9/Tn75O+M/S0efPlCkWBQdf3mfwtkK887z79h+TBFJURR+RUQkRbhw4QJff/01L7zwAjVq1LD9ABERMGAAlC9Pr7UvkzmztavxxO0T2Xt+LzM7zVRrM5FngDa5EBGRFGH48OHcuHGDESNGJM4APj5w7BjbO3/FoqX2fPYZ2Ge4wsDVA6njVof2pdonzrgikqIo/IqISLI7fvw448ePp3v37pQsWdL2A1y9CkOHYtarT7dpzShcGN56C75Y+wWXQi+ptZnIM+SR4dcwjPSGYWwxDGOXYRj7DMMYcuv4YMMwThmGsfPWq0XiT1dERNKizz77DAcHBwYNGpQ4A3z7LVy4wNwaI9m7z2DkSAi6fpgfNv/A6x6vUylfpcQZV0RSnITU/IYDDUzTvG4YhiOw3jCMJbfeG2Oa5qjEm56IiKR1O3bs4M8//+STTz4hf/78th/g7Fn49lsi23Xif79WoWZN6NAB2k3/kHQO6fiiwRe2H1NEUqxHhl/TNE3g+q1vHW+9zMSclIiIPDs+/vhjsmfPTv/+/RNngKFDITycsXmHc+4czJ8Pq46vZN5/8/iywZfky5QvccYVkRQpQTW/hmHYG4axEzgPrDBNc/Ott94yDGO3YRiTDMPIFs+53oZhbDMMY9uFCxdsM2sREUkT/vnnH5YvX85nn31GlixZbD/AoUPg48O1l735dHIxXn4ZKntG896y93DL4sZ71d+z/ZgikqIlKPyaphltmqYHUACoahhGWeAnoAjgAZwBvo3nXB/TND1N0/TMlSuXTSYtIiKpX0xMDB9//DFubm707t3bthePioL166FXL0ifno9vfA7AiBHw645f2XN+D980/ob0DultO66IpHiP1efXNM0rhmH4Ac3urvU1DGMCsNDGcxMRkTRsxowZ+Pv78/vvv5MunQ366549C0uXwpIlsHw5XLkCDg4EvjOa8d/m4dNPIUvuED6b/hm1XGvRsXTHpx9TRFKdR4ZfwzByAZG3gq8z0AgYaRhGPtM0z9z6WDtgbyLOU0RE0pCIiAgGDBhAhQoV8PLyerKLREfDli2weLH12r7dOp4vn/VEW/PmmA0b8UqbLOTObe1q/MW6L7kYepElTZeotZnIMyohK7/5gCmGYdhjlUnMME1zoWEYUw3D8MB6+C0AeDPRZikiImmKj48Px44dY8mSJdjZPUbL+QsX7qzuLlsGwcFgbw/Vq8OXX0Lz5lChAtwKtnNmw7p18MsvcD7yKN9t/o5uHt2o/FzlRLozEUnpDKuZQ9Lw9PQ0t23blmTjiYhIynPt2jWKFClC2bJlWbly5cNXYGNiYNs2a2V3yRLYuhVME/LkgWbNoEULaNwYst155vrqVVixAhYuhDlzoEAB2LkTuszuwLIjyzjU9xDPZXou8W9URJKVYRj+pml63n/8sWp+RUREntaoUaO4cOECI0eOjDv4XrpkreouWWKt8l68aK3kVqsGQ4ZYgbdiRbhrxfjYMSvsLlwIfn4QGWnl4ZYtYcAAWH/Sj9kHZvNF/S8UfEWecVr5FRGRJHP27FmKFi1Ky5YtmT59unUwJgZ27Lizurt5s3UsZ847q7tNmkCOHLHXiYqCTZtgwQIr8O7fbx0vWRJat4ZWraBGDXBwgOiYaDwneBIcFszBPgdxdnROhjsXkaSmlV8REUl2w4YNIzw8nC8//BBmzLgTeM+ft1Z3q1SBgQOtwFu5slXPe8uVK9aC8MKF1mnBwVa4rVsXeva0Am/Rog+O+dvO39h5difTOkxT8BURhV8REUkCpkng/Plk+/lnDuTJQ5Fq1axuDdmyWau7zZtD06aQO/c9px0+fGd1d906a8U3Z04r6LZqZS0IP2xvjKvhVxmwagDVC1SnS5kuiXyTIpIaKPyKiEjiuHHDWqpdtAiWLMHtzBm+ACJz5YLu3a3V3apV71ndjYyEf/+9E3gPHbKOly0LH35oBd7nn7/nlHiFRYYxYOUAzt04x/yX5qu1mYgACr8iImJLFy5YyXXuXKvlws2bkCULl6pUod+ZM5Tt148PRo2655TgYKvyYeFC6/m2K1fAyQnq14e337YeWnN3T9jwp6+dZuGhhSw4tICVx1YSFhXG6x6vUzV/VVvfqYikUgq/IiLydI4ds8Lu3LnWsm1MDLi5wZtvwgsvYNasSccmTdiXKxc/DhqEacLBg3dWd2+fkicPtG9vre42bgwZMz56aNM02X5mOwsOLWDhoYX4n/EHwD2rOz0q9aBV8VY0KNQgUW9fRFIXdXsQEZHHY5pW49y5c61Gunv2WMfLl4d27eCFF+7ZaGLp0qU0b96GPn1m4ODwAgsWWHkZwMPjTncGT897upfFKywyjJXHV7LgvwUsPLyQ09dOY2BQvWB1WhVrResSrSmTq4zKHESecer2ICIiTy4qynri7PYKb1CQlVRr1YLRo6FtWyhc+J5TfHz+5tNP/+XSpZrARcaNy0z69NCw4Z363QIFEjZ8XOUMGZ0y0rRIU1oXb02LYi3IlSGXre9aRNIghV8REYnbjRuwfLkVdhcutIpz06e3WiwMHmyl11z3Bs4LF2DePPjhh9Ps2fMC0Ak4BUzDyWkF48Z15I03Xnzk0I8qZ2hdvDV13OqQziGdjW9aRNI6lT2IiMgdFy9aQXfuXCv4hoVZ7chatbLKGZo2hQwZ7jnlzBmr+mHWLGt3tZgYsLM7TkzMDGAWsDX2s25ubgQEBMQ5dGhkKKuOr4qznKF18da0Kt5K5QwikmAqexARkbgdP24t186da5U2xMRAwYLQo4cVeGvXBkfHe045ccIKu7NmWQ+smSbkzh2Mq+siTpz4nuho/ziHCgoKuuf7uMoZMjllomnRprQq1krlDCJicwq/IiLPGtOEXbvu1O/u2mUdL1cOBgywAm/FirEPrN127JgVdmfOhC1brGO5cp0mR45ZXLz4E+fPH6BMmTJ8+GFrJk8+yblz5x4YuqBrQfxP+z+0nKGue12c7J0S7/5F5Jmm8CsiaZdpwsmTVg8tp2c8TEVFWUu0twNvQIAVbmvWhFGjrAfW4tgb+ODBO4F3507rWPbsx3B2/oOwsKlcuRJI3bp1ad26F61ataLwrYfeypYti7e3N6GhoeAIFAKH0g5cq3wNzwmeseUMIxqOoHXx1pTOVVrlDCKSJBR+RSRtOXMGVq6Ef/6xXqdOWfvftmplteFq1uyBmtU06/p162cwb57VVPfSJUiXDho1gs8+s34mefLcc4ppWp3Lbgfe/fut41my7MXObgoxMX9jGNfp2LEFrVt/SdOmTcmcOfMDQ7do34KuV7syddtUwvKFgSM4GA40LNGQ1sVb07xoc5UziEiyUPgVkdQtJATWrLkTeG+ntRw5rJ5aNWpYS5YLFoCv751uBe3aWQ1mc+RI1unblGla+wEvXmy91q6FiIg74f/2A2uZMj1wmr//7Rpek8OHDQwjBmfnbcDvwByeey4LrVu3pnXrP6hevTr2cewvfOHGBeb9N4+Z+2ey8vhKomKicC3nStsSbVXOICIphsKviKQu4eGwadOdsLtlC0RHg7Mz1KkDr71mrWxWqHDvjglRUbB+vdWWYM4cmD8f7O2th7lub8zg6ppcd/XkwsKs8H878B49ah0vXdraG7hFC6u04b6yj5gY2LzZWt2dOTOGoCA7DCMaB4e1wDTs7BZSvXppWrduTatWaylSpEicw5+5doY5B+cwc/9M1gSuIcaMoUi2IvSr3o8OpTrg+ZynyhlEJEVRqzMRSdliYmD3bivorlxprWaGhlrBtmpVK+g2bAjVq1u/0k8I04Tt2+8E4durxZUrW0G4XTsoVeqBB75SjMDAO2F35UorADs7Q4MGVtht3hwKFcLX15cBAwYQFBSEq6srw4Z9iavry8ycCX//HcW5cw4YRgSwAtOcSdas62jVqjqtW7emadOmZMmSJc7hg0KCmH1gNrMOzOLfoH8xMSmZsyQdS3WkY+mOlM9TXoFXRJJdfK3OFH5FJOU5fvxOze6qVVbvWbACaaNG1qtuXevX+bZw6NCdILx5s3WsePE7QbhKlYTtu5tYIiOth9UWLbIC7+2wXqgQtGxpverWtQLwLb6+vrceOIsA6gEdgReAPBjGTUxzMTCLYsUO8cIL9WndujXVq1fHwSHuXwgeDT7KrAOzmHVgFltOWa0eyucpT8dSHelQugOlc5VOvPsXEXkCCr8iknJdvGiF3NuB9/hx6/hzz90Juw0aQP78iT+XU6fu9Lxdvdoql3juOass4oUXoF69B3reJoozZ2DJEivsrlgBV69a49ata63utmhhBfQ4VlivX4dChXpx8WJNoCWQHbgOLARmUbv2Ddq1a0zr1q0pGkeHh9sOXjzIrP2zmHlgJjvP7gTA8znP2MBbNHv854qIJDeFXxFJOW7csDZTuF23e7uHVubMUL/+ncBbosQTlR5ERsKGDbBsmVUlUaSI9Yxbo0YPNDd4uMuXrdXWOXNg6VKr3CJr1judI+LY7eyJRUdb9cu3yxm2b7eO589/J+w2bPjAw2q3nT1rPdM3a1Y0q1ZBZKQ9cAkr8M4BlgE3MQyDmJiYOK9hmiZ7zu+JDbz7L1grzDUK1qBDqQ60L9Ue96zutrlfEZFEpvArIsknKgq2br0TdjdssBKqk5PVjeF22K1cGeL5tfujBARY+XTZMmuYa9esS1WuDEeOWF2+ADw8rCDctKn1HFhCy4QJC7O2+50zx0qZwcFWmcHdnSOyZ3+8SV+6ZE148WJr8pcuWeUVNWrcCbzly8f7D4CDB61F6jlzotmyxQ7TNDCM45jmXAxjPqa5Doi+55z7txc2TRP/M/7M2m+VNBwOPoydYUdt19p0LN2RdiXbkT9zEqy4i4jYmMKviCStmBgr2E2caAXeq1etEFexorWC2agR1KoFLi5PdPnQUKvJwbJlVm787z/ruJub1cq3WTOrUiJzZmsqO3ZY2XXZMqt8NirKyq716ln5tUmTx3jGLSrKWrm+XSd88qTVOaJu3TudIwoUePA807RWuW/X7m7ebE0uZ07rIbWWLaFx43hDdEyM1ejCCrwxHD5s1SHb2W0nJmYO2bOvo1OnUnTu3IlTp07Rq1cva5OJW1xcXPDx8eGll19i88nNzNw/k1kHZhEYEoi9YU+DQg3oWLojL5R8gdwZcj/W/x4iIimNwq+IJI3Ll2HyZPjpJ2vJNU8ea/ewRo2skoacOZ/osqYJBw7cWd1ds8bqepY+vRVgbwfeeMpg73HtmnX+8uXW63ZwLlDgThBu1CiBLYBvN8m9HYQPHLCOV6liBeEWLayfw+LFVg3vmTN33r+9uuvpGe8DdTdv3tmnYv78GM6ft8MwojCMNcTEzCZHjg106lSNzp07U6dOnXv6797d7aGgW0FeGfAKV/NfZfaB2Zy6dgpHO0eaFGlCh1IdaFOiDTlc0lDPYxF55in8ikji2rkTxo2zNpIIC7NWdfv0gfbtn3hr4StXrBKG26u7J05Yx0uVuhN2a9e+p8nBEwkIsJ4pW77cCppXrlgBunJlqzyiSROoVi2Bt/Hff3eC8JYtd45nyWJdrEULa+IPKT4ODrYWh+fOhWXLTG7cMHBwCMU0FxMdPYucObfRqVNjOnXq9EDgvVtEdARrAtYw68As5hycw/kb50nvkJ7mRZvToVQHWhVvRZb0NuqYISKSwij8iojtRURY24KNHWvV8To7Q9euVuitUOGxLxcTYz3ndXt1d+NG6zmwzJmtldhmzaz8mJC9KC6FXmJ90Hq2nt5KsezFaFa0GXkyPvppt+ho2LbtTonEpk3WsYwZrYXr2yvDxYoloETi1CkrVRcubNXxPqSeOSDgTpOJdetMoqMN0qe/RGTkbKKjZ5I79wE6dmxNp06dqF27dryB98rNKyw5vIR5/81jyZElXA2/SgbHDLQs3pKOpTrSvFhzMjplfOTPQUQktVP4FRHbOXUKfvkFfHzg3DmrnUKfPtbuatmyPdalzp27EzSXLbvT0rdy5Turu88//+juYidCTrAuaB3rAtexLmgd+y7se+AzlfNVpnnR5jQv1pzn8z+PvV3cAfJuISFWx7PbJRK3N1Bzd78ThBs0eOzbxjStOuR586zXrl3W8cyZgwgN/YuoqJnkzn2Cjh3b07lzZ2rVqhVv4A0KCWL+f/OZ9988/AL8iIqJIneG3LQu3pq2JdrSqHAjnB2fcnlcRCSVUfgVkadjmuDnZ5U2zJ1rLdO2bGmF3iZNErwJRGSktaJ7e3X3dkev3LmtyzRrZj3zlfshz1uZpsmhS4dYF7SOtYFrWRe0joArAQBkcspETdea1HatTR23OlTOV5kDFw+w5PASlhxZwsaTG4kxY8iWPhtNijShedHmCV4VBiv83g7Ct7tK3N5s7nYXiapV417kjYy0Wq/NnWsF3hMnwDBMsmc/QEjI70RFzSRv3ht06NCBTp06xRt4TdNk59mdzPtvHvP+mxfbg7dkzpK0Kd6GtiXbJjjci4ikVQq/IvJkrl2DqVOt0Lt/v9WJoHt3+N//rB3GEiAw8E7Y/ecf65L29larsaZNrcDr4RF/fo6OiWbXuV2xq7rrgtZx/sZ5AHK55KKOWx1qu9amtlttKuSp8NDQdznsMiuOrWDJkSUsPbKUs9fPAlApXyVrVbhoc54v8DwOdo9uuRYZaZX1LltmheGtW61/E2TObDW0yJp1C8uWfcLp0zlwcXkZaE5oaDocHaPIkWM7Fy9OJCpqDvnyOcYG3po1a8YZeG/X787/bz7zD80nKCQIA4MaBWvQtkRb2pZsS/EcxR85ZxGRZ4XCr4g8ngMHYPx4mDLFSquVKsFbb8GLLyboCbOQEOtUHx/Yd6sCwdX13jZk8e1OHB4VztbTW2NXdTec2MDV8KsAuGd1j13Vre1am+I5imM8wUYYADFmDLvO7mLJkVurwic2Em1GkzV91thV4aZFmpIvU74EXS842NqobvlymD37Bpcu3b0BxkUMYyGGsYCYmKXky5eFDh060LlzZ2rUqBFn4A25GcKSI7fqdw8vISQ8BGcHZ5oUaULbEm1pVbwVuTLkeqJ7FxFJ6xR+ReTRoqKsDRzGjbN+p+/kBJ07W6UNzz+foCa4+/dbz7/9/ru1kdvzz1t5uVmz+DdsuxZ+jQ0nNsSWMWw5tYXw6HAASucqTR3XOtR2q01t19oUzFLQ1ncd68rNK6w4emdV+Mx1qy2ZR16P2FXh6gWrJ2hV2M3NnaAgJ6AOcAjYAESTKVMmFi1aRM2aNbGLY6n7dv3u/P/m4xfgR2RMZGz9bpsSbWhUuBEujk/WG1lE5Fmi8Csi8Tt/3tqM4uefrULUggWhVy/o0ePhxbe33M7MY8daK5/p0sFLL1mZ2fOB/9uBCzcu3PNw2o6zO4gxY7A37KmUr1Lsym5N15rkdHmyvsBPyzRNdp3bFVsrvOHEBqLNaLKky0LjIo1ja4Wfy/TcPefFxMSwePFiWrduHed1799e+PY48w5a9bs7zu4AoESOErHlDKrfFRF5fAq/InIv07R2GBs7Fv7+22pb1rChVdrQqlWCthm+eNHKzD/9BEFBVmbu3dsqCc5112/jA68E3vNw2sGLBwFI75CeagWqWfW6rrWpXrB6im3DdeXmFf459g9LDi9h6dGlnL52GoAKeSrQvGhzGhdqTMD6AEZ/M5p9+/Zhb29PdHT0A9dxc3Pj8NHDrAlcw7yD8+Ks321Tog0lcpZI6lsUEUlTFH5FxBIWBn/9ZYXe7dshUybo1s1KraVKJegS/v7W6dOmWbusNWgAffvem5n3nt+L725fpu+bzvErxwHIki4LNV1rxpYxVM5XmXQO6RLrThONaZrsPrebJUeWsPC/hVYHCWLgJmS+mJlOFTtRNn1ZBvQdcGd74XTgVMaJyi9XZn/k/gfqd1sWb6kthUVEbCi+8PvopR0RSRuOHbOWaCdNsp7MKl3aqu195RUrAD9CRIS1QDx2rLXxQ4YM1gpvnz7WpcDqtTtt7zR89/iy+9xu7A17mhRpwnvV3qO2W23K5S6XJn59bxgG+R3yE7YijANjDxBzI4ZSLUtRsEFB9uXax68XfgXA9TNXLu+4zLX018AdIuwjOBJzhA6lOtC2ZFvV74qIJAOFX5G0zDSt1gM//giLF1u9xF54wSptqFs3QQ+w3b+fRbFi8P331mJxlixW67AJ/jPx3ePL2sC1mJhUK1CNH5v/iN0BO74e8DVLg5bi6urK8OHD8fLySvz7TkQBAQF8++23/Prrr4SFhdG2bVv69+9P9erVAWtVeM/5PbG1wqejTlMim+p3RURSCpU9iKRVW7bAhx9auyrkyQPe3tarQIFHnmqasH69tco7e7a1vW/LllZmbtwYImJusvDQQnz3+LL48GIioiMokaMEXuW8eLncyxTJXgRfX1+8vb3v/NofcHFxwcfHJ1UG4N27dzNy5EimT5+OnZ0dXbt25cMPP6TUI0pFomKiEtQdQkREbEs1vyLPimPH4NNPYfp0q1PDoEFW1wYnp0eeGhoKvr5W6N29G7JmtUobevcGN/do1gSuwXe3L7MOzCIkPIS8GfPyUtmX8CrnRaV8lWL77QYFBVGxYkWCg4MfGKNAgQKcOHHC1nedKEzTZO3atYwcOZIlS5aQMWNG3nzzTd59910KJOAfESIiknxU8yuS1gUHwxdfWMnVwQE++ww++ihB9bzHjln7Wfz6K1y5AuXLw4QJ8NJLJoeu7mT8Hl+mzZ3G6WunyeSUiQ6lO+BVzov67vWxt7MnKiqK9evXs2jRIhYtWsTevXvjHevkyZNUrlyZBg0a0KBBA2rVqkWmBMwxKcXExDBv3jxGjhzJ5s2byZUrF1988QW9e/cmW7ZsyT09ERF5Clr5FUntbt60Au/w4da2aq+/DkOHQv78Dz0tJgZWrLBOXbTIKgfu0MEqbchf5jjT9v6J7x5fDlw8gKOdI82LNcernBeti7fG2dGZS5cusXTpUhYtWsTSpUu5fPkyDg4O1K5dm5YtWzJ69GhOnz79wLhZsmTBw8ODjRs3EhERgb29PVWrVqVBgwbUr1+fGjVq4JyAHeQSQ3h4OL6+vnzzzTccPHiQQoUK8cEHH/D6668n25xEROTJqOxBJK2JibFaln36KQQGWluoff01lCv30NNCQuC336xGD4cPW5URb74JnbpdZF3wDHz3+LLhxAYAarvWxqucF53KdCJb+mzs3r07dnV306ZNxMTEkDt3blq0aEHLli1p3LgxWW7tWfyomt/Q0FA2bNjA6tWrWbVqFVu3biU6OhonJydq1KhB/fr1adCgAVWrVsUpASUbT+Pq1av4+PgwZswYTp8+jYeHB/3796djx444JKDfsYiIpDwKvyJpiZ8ffPCB1XDXwwO++QYaNXroKfv2WYH39rbD1aqBd59QHMrMZ8ZBX5YeWUpUTBRlc5fFq5wXL5V9iZyOOVm5ciWLFi1i8eLFnDx5EoDKlSvTsmVLWrVqReXKlePcphesADxgwACCgoIe2e3h6tWrrF+/nlWrVrFq1Sp27tyJaZq4uLhQq1at2DKJihUr2iyQnjt3ju+//57x48cTEhJCgwYN6N+/P40bN46tXxYRkdRJ4VckLdi/H/r3h4ULre3Uhg8HLy+rZiEOpgnz58MPP9zZdrjLS1F4dl7J1pu+zDk4h+sR1ymQuQAvl30Zr/JeZArNFLu6u3r1asLDw8mYMSNNmjShZcuWNG/enHz58iX6rQYHB7NmzRpWrVrF6tWr2bdvHwCZM2embt26sWUS5cqVizd8x+fo0aOMGjWKyZMnExERQfv27enfvz9VqlRJjFsREZFkoPArkpqdOQODB1t7CWfMaJU6vP02PKQO1c/Pet5t61YoUNCkTa+tRJb0Zf6x6Zy7cY6s6bPSqXQnupTqgt1JOxYvWsyiRYs4cOAAAMWLF6dly5a0bNmS2rVrJ3rpwaOcO3cOPz+/2JXhI0eOAJAjRw7q168fWyZRokSJ2FXb+1eee/bsye7du5k5cyYODg5069aNDz74gOLFiyfnrYmISCJ44vBrGEZ6YC2QDqs7xEzTNAcZhpEdmA64AwFAZ9M0Lz/sWgq/Io/p+nUYNcp6hYdbPccGDoScOeM9Ze9e+Phj6yG2rAWOEV72FcKKbYAc4Gg40qZkG1q5tSL6YDTLFy9n2bJlhISE4OjoSN26dWMDb7FixZLwRh/fiRMnYuuFV61aFds+LV++fNSvXx8XFxd8fX0JCwu757z06dPzzjvv8M477yTJCraIiCSPpwm/BpDBNM3rhmE4AuuBd4D2QLBpml8ZhvExkM00zf4Pu5bCr0gCRUVZ2xAPGgRnz0LHjjBiBBQtGu8pJ09aH//tN3AptJucrT8jIOMCsAeOA3vA4bADbnncOHbsGKZpki9fvtiH1Ro1apTiWo4llGmaHDt2LLZEYtWqVZw7dy7OzxYsWJCgoKAknqGIiCQ1m5Q9GIbhghV+/wf8DtQzTfOMYRj5AD/TNEs87HyFX5FHME1rybZ/f6u+t0YNa9X31ta5cQkJgZEjYfSYGKILLeG5DmMIcliJEWlgbjdhM3DXXhNOTk589tlntGzZEg8Pj8eul00NTNPE3t6euP7/zTAMYmJikmFWIiKSlOILvwn6r55hGPaGYewEzgMrTNPcDOQxTfMMwK2vuW04X5Fnz7Zt0KABtG4NkZHWvsLr18cbfMPD4fvvoXCJUEas+Jl075cmqksrorMdpFPWTpjfmrCEe4IvQGRkJAMHDqRSpUppMviCFXBdXV3jfC++4yIi8mxI0H/5TNOMNk3TAygAVDUMo2xCBzAMw9swjG2GYWy7cOHCE05TJA0LCICXX4YqVax+ZGPHWl/btYM42m3dbu9brNJp3p0/gGs9CkKr/+GW14kWoS248eUN/n73bxyi4m4H9qyEv+HDh+Pi4nLPMRcXF4YPH55MMxIRkZTgsZZ9TNO8AvgBzYBzt8oduPX1fDzn+Jim6WmapmeuXLmebrYiacnly1av3hIlYM4cq4PDkSPQpw84OsZ5yqpVULbRDl6a8SonO7pj1BmBZ84SVN1blT1v72H56OU0adgEPz8/fvvtt2c6/Hl5eeHj44ObmxuGYeDm5ha7wYaIiDy7EvLAWy4g0jTNK4ZhOAPLgZFAXeDSXQ+8ZTdN86OHXUs1vyJY9QrjxsEXX8CVK9CtGwwbBgUKxHvKzl0xdP9qEdvTjYZCfqQjI5WM8gTOCOD0vtPkz5+fN998kx49etzTweBxNpkQERFJS56m20N5YArWM+N2wAzTNIcahpEDmAG4AkFAJ9M0g+O/ksKvPONME6ZPt1Z4jx+Hpk2t7YjLl4/3lP+O3aDbmClsNr6DHIfJGJ2PwhefY//UXURdj6Jhw4b07t2bNm3aaBteERGRu8QXfh/5X0vTNHcDFeM4fgloaJvpiaRxa9daJQ5bt0KFCrB8OTRuHO/H9588xRs/j2Vz1C+Q8zKZr5Yj04binPrnEIGZQunTvQ+9evWiZMmSSXgTIiIiqZ+WikRsKSrKargbGGi9AgJg0yZYssQqa/jtN+jaFezt4zx9Y6A/b/0xhu3h08E+hoxn6hG17hhXD++hsIcHg3+ZwEsvvUSGDBmS9LZERETSCoVfkccRFgZBQXfC7d0hNzAQTp2y2jHcLX9++PJLePfdOLcjjo6JZt7BBXy6YAz/3VwL4ZlIt68T4Wt3EBG6ni5dutD792k8//zzsdv2ioiIyJNR+BW5W0jIg8H27tf9u4bZ21srum5uUK+e9fXul6srpE8f51DXI64zecdkvvL7ntM3j8IVN+y2fEiM/xby5dvI/z75H6+//jrqkiIiImI7Cr/y7DBNuHjxwdXau19Xrtx7Trp0VoB1d7c2n7g/3ObPD4/5oNmJkBP8uOVHftriw/WoEDhRHTa+DwfX06zZAfrM/oimTZtiH09phIiIiDw5hV9J206dIubtvhj792MEnYDQ0Hvfz5TpTpCtVevBcJs7NzzFLmh3txrLUykP7i+5s/XGVqKjgf3tYVN3XILX06vXSd5aOJxChQo93f2KiIjIQz2y1ZktqdWZJKlr15jiVYbe5U4Q6gSOph1OhgNO9k44OaTDyTG99bJ3SpTXpn838fO4nwk3wsETqyngzfSwvRds7sVzGTYzcKATr732AunjKY0QERGRJ/PErc5EUiMzMpJh71diUOUT1MlUjnoV2xERHXHvKybiwWO3Xjcib8T+OTI6Ms7PhEeHP3oiHW59vZwFlvSHHb1xiFnAvHkRtGjxaqL+DERERORBCr+S5kRGReA9sDy/FThCN+fq+Lzjh5O9k83HMU2TaDOaiOgIbkZGcPJMBMeDIgg4EUHgyQjG/PAH2OcCSsCZxmAuA2oTbeylRYuYR11eREREEoHCr6QpV8Ov0vGbKqxwPsSgyBoM+ny9TdqD3d++13peziAw0IHAQAeCglyIiLj/rPeAQOAo0BhYDYCrq9tTz0dERESejMKvpBknr56k5U+12B8RyKSznrz+8zpIYPC9eRNOnLi3AcTdfz51CushtbvkzWs9E1e5MrRvb/05PPwQP/3Un8OH/6FatbLs2rWLsLCw2HNcXFwYPny47W5aREREHovCr6QJu87uouVvjbl69QKL95Si8Yy193RpuH497lB7+89nz957PTu7O+1769SxOp09rH1vaGgogwYNYvTo0eTNm5d583xp06bNPd0eXF1dGT58OF5eXknxIxEREZE4qNuDpHrLjy6n4/QOZL4cyuJV+Si/dAfc2hhiwwbo0sUqWbibo+Od9r23A+3df86f3/pMQvj5+dGjRw+OHj1Kz549+eabb8iSJYtN71FEREQej7o9SJo0acckvBd4UybYgUWzM1FgxcrY4LtrF7RoATlzwogR9wbcvHmfqn0vACEhIXz00Uf4+PhQuHBhVq5cSYMGDZ7+pkRERCTRKPxKqmSaJoP8BjFs7TCaBGfj70nXybxoPpQoAcDhw9C0qbWHxcqVVuC1pYULF9KrVy/OnDlDv379GDp0KC4uLrYdRERERGxO4VdSnYjoCHrM78HU3VN542oRfh57FMff/7CKc7EeTmvc2HpAzc/PtsH3woULvPPOO0ybNo2yZcsye/ZsqlatarsBREREJFE95S9+RZLWlZtXaO7bnKm7pzLUrMfE0UdxHDIMbj1EdvGiFXyDg2HpUihZ0jbjmqbJn3/+SalSpZg5cyZDhgzB399fwVdERCSV0cqvpBpBIUG08G3BoUuH+D2nN6+85QOvvQYDBgBw7ZpV43vsmBV8K1e2zbgnT57kf//7HwsXLuT555/n119/pUyZMra5uIiIiCQprfxKqrDjzA6qTazGyasnWVr2K155bzI0aAC//AKGwc2b0LYtbN8OM2ZAvXpPP2ZMTAy//PILpUuXZuXKlYwePZp///1XwVdERCQV08qvpHhLDi+h09+dyO6cnX/r/U6Z5t2gWDGYNQucnIiKghdfhNWrYepUaNPm6cc8fPgwPXv2ZM2aNTRo0IAJEyZQuHDhp7+wiIiIJCut/EqK5uPvQ+tprSmeozib2i6gzEvvQLp0sGgRZM1KTAz06AHz5sEPP0DXrk83XlRUFN988w3ly5dn586dTJw4kX/++UfBV0REJI3Qyq+kSKZp8tmqz/hy/Zc0K9qMGS1/I1PTNnDuHKxZA+7umCa8/z5MmQJDhkDfvk835q5du+jevTv+/v60bduW8ePH89xzz9nmhkRERCRF0MqvpDjhUeF0ndOVL9d/iXclbxZ0mUem7r1h61aYNg2qVAHgiy/g++/hnXdg4MCnGC88nIEDB+Lp6cmJEyeYMWMGc+bMUfAVERFJg7TyKynK5bDLtJvejjWBaxjRcAT9a/bH+PBDmD0bxoyxnmoDfvwRPv8cXn0VRo8Gw3iy8TZu3Ej37t05cOAAr7zyCmPGjCFHjhw2vCMRERFJSbTyKylGwJUAak6qycaTG/Ft78vHtT7G+Okn+PZbeOsta4kX+OMPePttKwf/+uuTbVN8/fp13n33XWrWrMmNGzdYsmQJv//+u4KviIhIGqeVX0kRtp3eRqs/WxEeHc7yrsup617Xeqitb19o1Qq++w4MgwULrNa+9evDX3+BwxP8DV6xYgXe3t4EBATQp08fRowYQaZMmWx9SyIiIpICaeVXEpWvry/u7u7Y2dnh7u6Or6/vA59ZeGghdX+ri7OjMxve2GAF3x07oEsX8PCw6nzt7fHzg06doFIlq7tD+vSPN37BggWpW7cuTZo0wcnJibVr1zJ27FgFXxERkWeIVn4l0fj6+uLt7U1oaCgAgYGBeHt7A+B1azvin7b+xFtL3qJi3oosfHkheTPmhZMnrdXe7Nlh4ULImBF/f6t/b+HCsHgxJCSv3j/+yZMnOXnyJG3atGH69OmkT0h6FhERkTTFME0zyQbz9PQ0t23blmTjSfJyd3cnMDDwgeN2dnZkz5GdsJph3PC4gfMJZ/Kuz4sTTmQGpgYGkj8igp6lShGQKRPh4YXYu3c89vY3qVq1HxkyXMbBwQF7e/t4v9rb2+Pr68u1a9ceGN/NzY2AgIDE/wGIiIhIsjEMw980Tc/7j2vlVxJNUFBQnMdj7GLI8kYWLjpfpOS1knhGehJTOQYiI/lg7VqKhoczpGpVQrJnx+FadnbsGA1EU7r0u4SHBxAaGk1UVBTR0dFER9/58/1f4wq+D5uXiIiIpH0Kv5IoVqxYQZy/VXCGdN3ScdT5KF83+poPanyAYRhgmtCrl7WJxYQJDO3Rg/PnoVYtq7Z3zRqoUOGvx5pDfCvPrq6uT3pbIiIiksrpgTexuVWrVtGmTRsKFiyIs7PznTeygdHTICZfDNM7TufDmh9awRfgm2/Axwc++QR69CAkBJo2tcp/Fy2CChUefx7Dhw/HxcXlnmMuLi4MHz78Ke5OREREUjOFX7GpNWvW0KpVK4oWLYq/vz8TJkzAzc0N8oOdtx0ZcmZg1Wur6Fym852T/v4b+ve3ujt88QWhodC6NezbZ+1tUbPmk83Fy8sLHx8f3NzcMAwDNzc3fHx8Yh+2ExERkWePHngTm1m3bh3NmzfHzc2N1atXkzt3bgDmHZzHS7NeIm/GvCzxWkKJnCXunLRhAzRoAJ6e8M8/RNilp107WLLE6nDWpUsy3YyIiIikavE98KaVX7GJDRs20KJFCwoUKMDKlSvJnTs3YZFhfLj8Q9pNb0e5POXY1GPTvcH36FFrm7aCBWHuXKId09Otm9XK7KefFHxFRETE9vTAmzy1zZs306xZM/Lly8eqVavImzcv6wLX0X1+dw4HH8a7kjdjmo3BxfGu+ttLl6BFC4iJgcWLMXPkpG8fa9e2ESPgzTeT735EREQk7VL4laeybds2mjRpQu7cuVm9ejWZc2am7+K+jN06lkJZC7Hy1ZU0KNTg3pPCw6FdOwgIgJUroVgxBn5mrfZ+9BF8/HGy3IqIiIg8AxR+5Ylt376dxo0bkyNHDlavXs3B8IP0+KkHgVcCebvq23zZ8EsyOGW49yTThDfegHXrrKLeWrX49lsYPhx69ICvvkqeexEREZFng8KvPJFdu3bRuHFjsmTJwrxl8xi2cxgTtk+geI7irH19LbVca8V94qBB8OefVtp98UUmTYIPPoBOneDnn+F25zMRERGRxKDwK49tz549NGzYEBcXFz6f+jktFrbg9LXTfFTjIwbXG4yzo3PcJ06eDMOGQffu8MknzJoFPXtCkyYwdSrY2yftfYiIiMizR+FXHsv+/ftp2LAhjpkdqTK4Ct1XdadMrjLM6jyLqvmrxn/iypXg7Q2NGsFPP7HiH4OXX4bnn7d6+aZLl3T3ICIiIs8uhV9JsIMHD9KgQQMii0TCC7AgcAED6wxkQO0BpHN4SHrdvx86dIASJWDmTDb5O9KunfXtokWQIUP8p4qIiIjYksKvJMihQ4eo26IuIY1CCC8WjkdWD5a3XY5HXo+Hn3jihNXSzNkZFi9m74kstGgBefPCsmWQLVuSTF9EREQEUPiVBDh8+DDVelTjSucrOGRw4Iu6X/BRzY9wtHd8+IkHDlgFvVevwsqVHItypUkTSJ8eVqyAfPmSZv4iIiIityn8ykNt3reZ+qPqE9YwjLLZyvLXi39RJneZR5+4ZYu14uvgAGvWcCaPB41rWS1+166FQoUSf+4iIiIi99P2xhIn0zQZvXI0NXxrEFYgjPfKvMeOt3YkLPiuWAENGkDmzPDvvwS7etCkCZw7Z21dXCYBlxARERFJDI8Mv4ZhFDQMY7VhGAcMw9hnGMY7t44PNgzjlGEYO2+9WiT+dCUpnAg5QcNJDem3vh/GRYPZjWczuuNoHOwS8IuC6dOhZUsoUgT+/ZeQnEVo2RIOHYJ586zuDiIiIiLJJSFlD1FAP9M0txuGkQnwNwxjxa33xpimOSrxpidJyTRNJmyfQL9l/bgRdoP0a9Pj940fz1dNYGIdPx7eegtq1YL58zl+OSutGlnBd8YMaNgwcecvIiIi8iiPDL+maZ4Bztz68zXDMA4A+RN7YpK0jl8+To8FPVh1fBXOZ51xWejCP3//k7Dga5owZIj1at0apk9n405n2raFyEirq0ODBol/DyIiIiKP8lg1v4ZhuAMVgc23Dr1lGMZuwzAmGYYRZ9MqwzC8DcPYZhjGtgsXLjzdbMXmYswYftz8I2V/KsuWk1vIuzUvdn/YsXz6cqpVq/boC0RHW6u9Q4bAa6/B7Nn8OceZ+vUhSxbYvFnBV0RERFKOBIdfwzAyArOAd03TvAr8BBQBPLBWhr+N6zzTNH1M0/Q0TdMzV65cTz9jsZlDlw5R97e6vL30barnq06+2fm4uvoqSxYvoUaNGo++QEQEeHlZ5Q4ffID56yQGf+GAl5dV27tpExQvnvj3ISIiIpJQCQq/hmE4YgVfX9M0ZwOYpnnONM1o0zRjgAnAQ/a2lZQkOiaaURtGUeHnCuw9v5cfG/7I2dFnObn/JIsWLaJ27dqPvsj169CqlfWA29dfc3PYN3h1NWIXgFesgBw5Ev1WRERERB7LI2t+DcMwgF+BA6Zpjr7reL5b9cAA7YC9iTNFsaV95/fxxvw32HJqC21LtOXLml/ycuuXOXrkKAsXLqRevXqPvsjFi1ZHh23bYNIkzrV4nRfqWyu9I0ZA//5gGIl+KyIiIiKPLSHdHmoCrwB7DMPYeevYp8BLhmF4ACYQALyZCPMTG4mMjuTrf79m6NqhZE6Xmb86/EXj5xrTuHFjDh48yPz582mYkHYMQUHQtCkcPw5z5rC3cBtaPQ/nz8PMmdChQ+Lfi4iIiMiTSki3h/VAXOt4i20/HUkMO8/u5I15b7Dj7A66lOnCj81/xDHSkcaNG7N3717mzp1LkyZNHn2hu7crXr6cpaF16FwDMma0dm3z9Ez8exERERF5GtrhLY1bemQpVSZU4fS108zuPJu/Ov5Fuuh0NGvWjF27djFr1iyaN2/+6Att2QK1a1u9y9asYezuOrF7WWzZouArIiIiqUNCyh4klTp2+RgvzXqJ0rlKs7rbarI7Z+fatWs0b94cf39/Zs6cSatWrR59oeXLoX17yJOHqMXLeW9sEcaOtVr6/vmntfIrIiIikhpo5TeNCo0Mpf309gDM6TKH7M7ZuX79Oi1atGDz5s389ddftG3b9tEXmj7d6upQpAjXlqyn9btW8O3XD+bMUfAVERGR1EUrv2mQaZp4L/Bm97ndfJDvAxpUbEBQUBBOTk6Eh4czffp0OiTkybS7tisOGjufFu2z8t9/4OMDPXsm/n2IiIiI2JrCbxo0dstYfPf40iF7B8a9N47Q0FAAwsPDcXJyIjIy8uEXuG+74s3vT6dNY2fCw2HpUkhIUwgRERGRlEhlD2nMusB1vL/8fVoXb83Wb7fGBt/bIiIiGDBgQPwXuG+74uldZlO3mTOZMll9fBV8RUREJDVT+E1DTl87Tae/O1EoayGmtpvKiaATcX4uKCgo7gvctV2x2e8DhrpP4sWuDlStagXfkiUTcfIiIiIiSUBlD2lERHQEnf7uxPWI68zvOJ+BHw3ENM04P+vq6vrgwevXrY4OK1YQOfxrXtv3IX9+C6++atX4pkuXyDcgIiIikgQUftOI95e9z4YTGxhSbghejb04cuQITZs2Ze3atYSFhcV+zsXFheHDh9978sWL0KIFbN/O1e8m0XzG62zYAF9+CR9/rK2KRUREJO1Q2UMaMGXnFMZtHUfliMoM7jiY6Oho/Pz8WLp0KRMmTMDNzQ3DMHBzc8PHxwcvL687JwcFWZtX7N5N0HezqfDd62zfDn//DZ98ouArIiIiaYsR36/GE4Onp6e5bdu2JBvvWbDjzA6qT6yO/Rl7Qn8JpZd3L7755hsyJqQB713bFW8ZuIDGw+rg4gLz50OVKok/dxEREZHEYhiGv2maD+xBq7KHVOz0ldPU/6U+4VfDybciH3OXzqVx48YJO3nzZqvUwdGR6X3W4vVxBcqUgQULIK6SYBEREZG0QGUPqdS27dso8WkJQqJDaB3WmgPbDiQ8+C5fDg0bYmbNytCm//LiiAo0bw7r1yv4ioiISNqm8JvKREZGMmTIEKr2r8r1PNd5q8hbzP9pPlmyZEnYBW5tVxxdqAhd3dYz6PcivPcezJ0LmTIl6tRFREREkp3KHlKRvXv30q1bN7aHbocX4ZXSr/Bjpx8TfoFx46BvX25WqUWDa/PZsjYrP/0EvXol3pxFREREUhKt/KYCUVFRjBgxgsqVK3P82nGcX3amynNV8Gnnk7ALmCYMHgxvvUVwrdaUOL6M/aezsmSJgq+IiIg8W7Tym8IdPHiQ1157jc2bN9O2c1sO1DzA5fDLzOo8i/QO6R99gZgY6NsXxo/neN3XKLtxAnnyO7BxEZQqlfjzFxEREUlJtPKbQkVHRzN69GgqVqzI4cOHmTZtGg4dHDhy5Qh/dfyLglkKJuxCQ4bA+PFsqPkBhddMolJVBzZvVvAVERGRZ5PCbwp05MgR6tWrR79+/WjSpAn79u0jqGAQsw7MYmSjkTQo1CBhF1q4EIYOZW3h16j579d07Wrwzz+QK1fizl9EREQkpVL4TUFiYmIYO3YsFSpUYM+ePUyZMoW5c+eyL3Qfn6z8hE6lO9Gver+EXezIEcyuXQnMUYmmx8YzbJjB779DunSJew8iIiIiKZlqflOIgIAAunfvzqpVq2jatCkTJ06kQIECBF4JpMvMLpTMWZJJbSdhJGS/4Rs3oF07bkbaUzdkFv0GOPPZZ4l/DyIiIiIpnVZ+k5lpmvj4+FCuXDm2bt3KhAkTWLJkCQUKFOBm1E06zOhAZEwkc7rMIaNTArYsNk3o2RNz3z7ahU2jcnt3hg5N/PsQERERSQ208puMTp48SY8ePVi2bBkNGjRg0qRJuLm5AVYo7r2oN/5n/Jn34jyK5yiesIv+8ANMm8ZQp+GcL9OEdb+Dnf6JIyIiIgJo5TdZmKbJlClTKFu2LOvWrWPs2LGsWLEiNvgC+Pj7MHnnZD6r/RltSrRJ2IXXrsX84AOWO7fll2wfM38+ZMiQSDchIiIikgpp5TeJnT17Fm9vbxYsWECtWrWYPHkyRYsWveczm05uou+SvjQr2ozB9QYn7MKnT2N27swJx8K8EjOFBfPtKFDA9vMXERERSc208puIfH19cXd3x87ODjc3N/r06UOZMmVYsWIFo0ePxs/P74Hge+76OTrO6EiBzAXwbe+LvZ39oweKiMDs2JHwS9dpHjabH6ZkoWrVRLopERERkVRMK7+JxNfXF29vb0JDQwEICgpi/PjxFClShA0bNlCiRIkHzomMjqTLzC4EhwWzsftGsjtnT9hg77+PsXEjrzCDToPK0KWLLe9EREREJO1Q+E0kAwYMiA2+d4uMjIwz+AL0/6c/awLXMLXdVCrkrZCwgX7/HcaN41v6Yde5E59//jSzFhEREUnbFH4TSVBQUJzHT5w4EefxaXumMWbTGPpW7UvX8l0TNsiOHcR4v8l6+3r87fEVqyars4OIiIjIwygqJRJXV9cEH99zbg89FvSglmstRjUZlbABgoOJeqED56Jy8FbO6cye74CLy9PMWERERCTtU/hNJC+++OIDx1xcXBg+fPg9x67cvEK76e3Iki4LMzrOwMne6dEXj44m+iUvYk6c4kWHWUxelJvnnrPVzEVERETSLoXfRBAcHMzUqVN57rnnKFiwIIZh4Obmho+PD15eXrGfizFj6Dq7K4EhgczsPJN8mfIl6Prm4CHYL19KX/MH+v7xPJUrJ9adiIiIiKQtqvm1MdM0+d///sf58+fZvHkzlSpVivezw9YMY9HhRYxtPpYaBWskbIAFCzC+GMYkXqfgUG86drTRxEVERESeAQq/NjZt2jRmzJjB8OHDHxp8Fx1axJA1Q3i1wqv0rtI7YRc/fJjIF7uym0qs6TSO3z4zbDRrERERkWeDYZpmkg3m6elpbtu2LcnGS2onTpygXLlylClThjVr1uDgEPe/LY4EH6HKhCq4Z3VnwxsbcHZ0fvTFb9wgzKMaN46coYeHP9M2uOGcgNNEREREnkWGYfibpul5/3Gt/NpITEwMr732GlFRUfz+++/xBt8bETdoP709doYdszvPTljwNU3CuvbA6ch+euRays9LFHxFREREnoTCr4388MMPrFq1igkTJlCkSJE4P2OaJj0X9GTv+b0s7bqUQtkKJejaEaO+x3nuXwxy/JIPlzcmb15bzlxERETk2aHwawP79u3j448/pnXr1nTv3j3ez/2w+Qem7Z3G8AbDaVKkSYKubfqtwb7/B8zhBTz++hgPDxtNWkREROQZpFZnTykiIoKuXbuSOXNmJkyYgGHE/RDamoA19FvejxdKvsDHtT5O2MVPneJGq84cMYtw7PMptGuvB9xEREREnoZWfp/S4MGD2blzJ3PnziVPnjxxfubU1VN0ntmZItmLMOWFKdgZCfg3R0QEl+p3JN2NG0xqtZqvBme28cxFREREnj1pfuXXjDG5evJqolx7/fr1jBw5ku7du9O2bds4PxMeFU7HvztyI+IGc7rMIXO6hIXY813fI8fhTYwoPpkhf5cmngVlEREREXkMaT78bh04nxhXN1Y1+pKQU9dtdt1r167x6quv4ubmxpgxY+L8zI2IG7ww/QU2ndzEby/8RulcpRN07cvfTSH33+P5JdMHvL22E+nT22zaIiIiIs+0NB9+s1YqzKHctWiwcgCRBQuxvNlorpwJe+rrvvfeewQGBjJ16lQyZcr0wPvBYcE0ntqY5UeX49PKh46lE7YVW9iGHTi/34s1dvWp7jeCeCopREREROQJpPnwW7xDOaqeXcDB3zZyMqcHTZb1Iyx/ERa3HMeVc+FPdM158+bx66+/0r9/f2rWrPnA+6eunqLO5Dr4n/Hn705/07NyzwRdN+bCJa41bs8FMydhk/+ifCWVZIuIiIjY0iPDr2EYBQ3DWG0YxoH/t3fv0VGUeRrHv78QEg2IIARFgYAHQbkj2QFXZmDFMXiDWUZUTlAEARlhV5n1NqIugtlFxZHxMuOJRsJKRlDRBbyQiawMoK6zAUYEo9xUQBECBCEiBsi7f3Tl2CBgLpWudOr5nNMnlbe63n6f7s7bv66u6pjZOjO7zWs/w8wKzGyD97NZ7Q+3+s4f2ZeeOwtYn72UPWd04Io3J7K/VUcWDM5hb/GhSvezY8cOxo4dS8+ePZkyZcqP1m/YvYF+s/rxxTdf8FbmWwy9YGjlOj5yhM0XZXL6ga9YOnE+g25sWekxiYiIiEjlVGbP72Hg35xzFwB9gQlm1hm4B1jinDsPWOL9Xud1HNufLsV/ZePT+XzX9CyGLBrDnrMu4NWhc9i7+8hJt3XOMXbsWPbt28ecOXNISko6av3q7avpN6sfpWWlvDPyHS5pf0mlx7Vu2BQ6bMrnxYueZMQTP6tWNhERERE5uZ8sfp1z251zq7zl/UARcA4wBJjtXW028KtaGqP/zOhw62V03P2/bJ65EDutMUNfu4GvW3Zj3rBXKNldftzNcnJyWLRoEdOnT6dLly5HrVv6+VL65/YnuUEyK0atIP3sH/0r6RPaMGMBXV57iNfPHM3w/xmrb3YQERERqSXmnKv8lc3aAcuArsAW51zTqHUlzrmTHvqQnp7uCgsLqzfS2lRezuePzSdx2gO03v8JaxJ68NGwaVzxx6todkakEt20aRM9evSgT58+FBQUkJDww/uGBZ8s4LpXruPcZueSPyKfNqe3qfRNf71sPSkD/oHPGnbk7I3LSW2jr3YQERERqSkzW+mc+9HeyEqf8GZmjYH5wO3OuUp/ca6ZjTOzQjMrLC4uruxmsZWQQLs7h9G6ZC1fZL1A6qmlZM4bzKbUvuRmFrBzxyFuuOEGEhMTyc3NParwnbV6FkNfGkqPs3qwfNTyKhW+3+4opTRjKIdoyCmLXlHhKyIiIlLLKlX8mllDIoVvnnPuVa95h5m18ta3AnYeb1vnXLZzLt05l56amurHmGtPgwak3TuCViVFbPv3Z0lL3s5Nf76MT1tdQuL7F/DII8/Rps0Pxe2M92YweuFoBrYfyJIbl9A8pXmlb6r8iOPv6WNof7CIjdPm0umytNpIJCIiIiJRKvNtDwbkAEXOud9HrVoIjPSWRwIL/B9eQBo2pPWUMaSWbGDlqPvo4NayjOfpcGs2z4z6gF27HHcX3M2dBXdybZdrWTR8EY2TGlfpJvIHPc7F2+bx/pVZ9Jl8aS0FEREREZFoP3nMr5n1A5YDHwEVZ4LdC3wAvAS0BbYAw5xze07WV5095vcEvvvuO3r37s33JSW8/esJNH/2D6Qc3sWVV7flL722cFPX8Tz3z0/RIKFBlfp9+76lDMi6lDVpg+m1eT6WoDPcRERERPx0omN+f/K/KDjnVgAnqs4G1nRgddm9995LUVERixcvpn1GBgen3cLgRwfwl+SPuf+v0HNaMU+O/pQR/9GZFi0q1+eqhdvolnUdX6acR9fCXBW+IiIiIjFU7//DW3UtWbKEmTNnMnHiRDIyMtj3/T6uWHgdbyV/zB/6T2dix/u53PL512e7UtDqBmaM38iuXSfvc8uG7ym/ZhiN7ACnv/0qSS2axCaMiIiIiABV/KqzmoqXwx5KSkro3r07jRo1YtWqVZS6Ui7Pu5w1O9aQOySXzO6ZkSvu2sWuux/ltNlP0uBIGXMSb2LH2Pu5eWraj/YEl5bCm+1+w7W7n2Hb4y/T+vZrYh9MREREJCRq/FVnYTJx4kS+/vpr5syZQ3FZMT+f9XOKiotYcP2CHwpfgBYtaJHzMMnbNvNN5gQyy19g0p/OY36riWRN+IqKb3YrL4fnf5HLtbuf4bNr7lThKyIiIhIQ7fk9xty5cxk+fDhTp05l6C1DyZiTwbeHvuX14a9zcduLT77x1q3suSOLJi/ncMgl8mzirey95W5S9mxj4ov/SHHHi2mzLh8Sf/JQaxERERGpgRPt+VXxG+XLL7+ka9eudOrUiRnzZjB47mCSE5PJH5FP9zO7V76jzZvZ+9upNFn4AgfcqZTSmKTGSTTbtBJrWce/61hERESkHtBhDz+hvLycUaNGUVZWxriHx5GRl0GzU5vx7uh3q1b4Apx7Lk3/O5eEj9dx5IqraZpSRpP8V1T4ioiIiARMn797nn76aQoKChjz+BjGLxtP59TOLB6xmLMan1X9Ts8/n9PfeBGcA9NXmomIiIgETXt+gaKiIu666y663NSFnG9y6Nu6L0tvWlqzwjeaCl8RERGROiH0xW9ZWRmZIzKxAca6duu4quNV5I/Ip+kpTYMemoiIiIj4LPSHPUydNpXVZ66GPnBjjxt57urnaNigYdDDEhEREZFaEOo9v8vfXU5WURb0gUl9JzFryCwVviIiIiL1WGiL350lOxk0exB0gwcufoDHLnuMBAvt3SEiIiISCqE87KHkuxK6z+jOgVYHuKPTHTx46YNBD0lEREREYiB0uzq/2v8VvZ7oxY6EHQw5NIRHr3806CGJiIiISIyEas/vxj0bGZg7kK37ttL+g/bMe2Ne0EMSERERkRgKTfG7evtqBuUNYu83e2mQ14AFixaQnJwc9LBEREREJIZCcdjDsi+WMWD2AA4fPEzZM2VM/5fpdOvWLehhiYiIiEiM1fvi980Nb5IxJ4PUU1I5+MeDDOg6gEmTJgU9LBEREREJQL0ufvPy8hgzbAwHPznI1ge3Ul5STm5uLgkJ9Tq2iIiIiJxAvT3mNy8vj3HjxnHgwAH4EMooIykpiRUrVpCWlhb08EREREQkAPV2F+jkyZMjhW+UsrIyJk+eHNCIRERERCRo9bb43bJlS5XaRURERKT+q7fFb9u2bavULiIiIiL1X70tfrOyskhJSTmqLSUlhaysrIBGJCIiIiJBq7fFb2ZmJtnZ2aSlpWFmpKWlkZ2dTWZmZtBDExEREZGAmHMuZjeWnp7uCgsLY3Z7IiIiIhJOZrbSOZd+bHu93fMrIiIiInIsFb8iIiIiEhoqfkVEREQkNFT8ioiIiEhoqPgVERERkdBQ8SsiIiIioaHiV0RERERCQ8WviIiIiISGil8RERERCQ0VvyIiIiISGip+RURERCQ0VPyKiIiISGio+BURERGR0FDxKyIiIiKhoeJXRERERELDnHOxuzGzYuCLmN1g3dEC2BX0IAIW9vtA+ZVf+cNL+ZVf+YOR5pxLPbYxpsVvWJlZoXMuPehxBCns94HyK7/yK3/Q4wiK8it/Xcuvwx5EREREJDRU/IqIiIhIaKj4jY3soAdQB4T9PlD+cFP+cFP+cFP+OkbH/IqIiIhIaGjPr4iIiIiEhorfajKz581sp5mtjWrrYWbvm9lHZrbIzJp47UlmNstr/9DMBnjtKWb2hpl9YmbrzGx6MGmqzo/8x/S3MLqvus6v/N66bDNb7z0Pfh37NFXnY/7hXvsaM1tsZi1in6bqzKyNmb1jZkXe3+5tXvsZZlZgZhu8n82itvmdmW00s0/NLCOqvbd3H2w0syfMzILIVBV+5Y/XOdDPxz9qfdzMgT4//+NuDvQ5f9zNgVXNb2bNveuXmtlTx/QVzPznnNOlGhfgF8CFwNqotv8D+nvLo4Fp3vIEYJa33BJYSeSNRwrwT157ErAcuDzobLHKH7XdUODP0X3V9Ytf+YEHgYe85QSgRdDZYpUfSAR2VmQGHgGmBJ2tkvlbARd6y6cB64HOXoZ7vPZ7gIe95c7Ah0Ay0B7YBDTw1v0NuAgw4K14mAP8yh+vc6Cfj7+3Pq7mQJ+f/3E3B/r4/I/LObAa+RsB/YDxwFPH9BXI/Kc9v9XknFsG7DmmuROwzFsuACrewXYGlnjb7QT2AunOuQPOuXe89jJgFdC6dkfuDz/yA5hZY+C3wEO1O2J/+ZWfSJH4n966cudcXHwRuk/5zbs08t7tNwG+qtWB+8Q5t905t8pb3g8UAecAQ4DZ3tVmA7/ylocAc51z3zvnPgM2Aj8zs1ZAE+fc+y7ySvBfUdvUWX7lj9c50K/8EJ9zoJ/5icM50Mf8cTkHVjW/c+5b59wK4GB0P0HOfyp+/bUWGOwtDwPaeMsfAkPMLNHM2gO9o9YBYGZNgavxioQ4VZ3804DHgAOxHGgtqVJ+7zEHmGZmq8zsZTM7M6Yj9leV8jvnDgG/AT4iMuF3BnJiO+SaM7N2QC/gA+BM59x2iLxAENnTDZEXhq1Rm23z2s7xlo9tjxs1zB/dT1PicA70IX9cz4E1yV8f5sCa5K8Pc2Al859IYPOfil9/jQYmmNlKIh8FlHntzxN5UAuBmcB7wOGKjcwsEXgReMI5tzmWA/ZZlfKbWU+gg3PutdgPtVZU9fFPJLKX613n3IXA+8CMGI/ZT1V9/BsSmfh7AWcDa4DfxXjMNeLttZsP3O6c23eyqx6nzZ2kPS74kL+in7icA2uaP97nQB8e/7ieA314/ON6DqxC/hN2cZy2mMx/ibG4kbBwzn0CXAZgZh2BK732w8CkiuuZ2XvAhqhNs4ENzrmZMRtsLahG/v5AbzP7nMhzsaWZLXXODYjtyP1Rjfy7ieztqXjhexm4OYZD9lU18vf01m/y2l8icpxYXPBeuOYDec65V73mHWbWyjm33ftIb6fXvo2jP+1pTWRPzzaO/pi/or3O8yl/hbibA33KfxFxOgf6lD9u50Cf8veE+JwDq5j/RAKb/7Tn10dm1tL7mQDcBzzj/Z5iZo285V8Ch51zH3u/PwScDtwexJj9VNX8zrk/OefOds61I3Iw/Pp4mPRPpBr5HbAIGOB1MRD4ONbj9ks1nv9fAp3NLNXr4pdEjh2r87zj83KAIufc76NWLQRGessjgQVR7debWbJ36Md5wN+8jwb3m1lfr88bo7aps/zK7/UVd3Ogj49/XM6BPuaPyznQx+d/XM6B1ch/XIHOf64OnDkYjxciH9FtBw4RefdyM3AbkbMe1wPT+eGfiLQDPiXypH4bSPPaWxPZxV8E/N27jAk6W6zyH9NfO+LkTGc/8wNpRE4SW0PkWMe2QWeLcf7xXvsaIi+CzYPOVsn8/by/3TVRf7tXAM29x3GD9/OMqG0mEznL+1OizmgmcvLfWm/dUxX3W12++JU/XudAPx//qPVxMwf6/PyPuznQ5/xxNwdWM//nRE6SLiXymtHZaw9k/tN/eBMRERGR0NBhDyIiIiISGip+RURERCQ0VPyKiIiISGio+BURERGR0FDxKyIiIiKhoeJXREREREJDxa+IiIiIhIaKXxEREREJjf8HdL9ZNXcU9b4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fit1 = Holt(air, initialization_method=\"estimated\").fit(smoothing_level=0.8, smoothing_trend=0.2, optimized=False)\n",
    "fcast1 = fit1.forecast(5).rename(\"Holt's linear trend\")\n",
    "fit2 = Holt(air, exponential=True, initialization_method=\"estimated\").fit(smoothing_level=0.8, smoothing_trend=0.2, optimized=False)\n",
    "fcast2 = fit2.forecast(5).rename(\"Exponential trend\")\n",
    "fit3 = Holt(air, damped_trend=True, initialization_method=\"estimated\").fit(smoothing_level=0.8, smoothing_trend=0.2)\n",
    "fcast3 = fit3.forecast(5).rename(\"Additive damped trend\")\n",
    "\n",
    "plt.figure(figsize=(12, 8))\n",
    "plt.plot(air, marker='o', color='black')\n",
    "plt.plot(fit1.fittedvalues, color='blue')\n",
    "line1, = plt.plot(fcast1, marker='o', color='blue')\n",
    "plt.plot(fit2.fittedvalues, color='red')\n",
    "line2, = plt.plot(fcast2, marker='o', color='red')\n",
    "plt.plot(fit3.fittedvalues, color='green')\n",
    "line3, = plt.plot(fcast3, marker='o', color='green')\n",
    "plt.legend([line1, line2, line3], [fcast1.name, fcast2.name, fcast3.name])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Seasonally adjusted data\n",
    "Lets look at some seasonally adjusted livestock data. We fit five Holt's models.\n",
    "The below table allows us to compare results when we use exponential versus additive and damped versus non-damped.\n",
    " \n",
    "Note: ```fit4``` does not allow the parameter $\\phi$ to be optimized by providing a fixed value of $\\phi=0.98$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:16.605618Z",
     "start_time": "2017-12-07T12:39:16.116424Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SES</th>\n",
       "      <th>Holt's</th>\n",
       "      <th>Exponential</th>\n",
       "      <th>Additive</th>\n",
       "      <th>Multiplicative</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>$\\alpha$</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.974316</td>\n",
       "      <td>0.977633</td>\n",
       "      <td>9.788623e-01</td>\n",
       "      <td>0.974913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$\\beta$</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.437128e-11</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$\\phi$</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.800000e-01</td>\n",
       "      <td>0.981646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$l_0$</th>\n",
       "      <td>263.917698</td>\n",
       "      <td>258.882555</td>\n",
       "      <td>260.344565</td>\n",
       "      <td>2.573572e+02</td>\n",
       "      <td>258.951736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$b_0$</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.010839</td>\n",
       "      <td>1.013780</td>\n",
       "      <td>6.645778e+00</td>\n",
       "      <td>1.038145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SSE</th>\n",
       "      <td>6761.350235</td>\n",
       "      <td>6004.138201</td>\n",
       "      <td>6104.194756</td>\n",
       "      <td>6.036555e+03</td>\n",
       "      <td>6081.995046</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  SES       Holt's  Exponential      Additive  Multiplicative\n",
       "$\\alpha$     1.000000     0.974316     0.977633  9.788623e-01        0.974913\n",
       "$\\beta$           NaN     0.000000     0.000000  7.437128e-11        0.000000\n",
       "$\\phi$            NaN          NaN          NaN  9.800000e-01        0.981646\n",
       "$l_0$      263.917698   258.882555   260.344565  2.573572e+02      258.951736\n",
       "$b_0$             NaN     5.010839     1.013780  6.645778e+00        1.038145\n",
       "SSE       6761.350235  6004.138201  6104.194756  6.036555e+03     6081.995046"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit1 = SimpleExpSmoothing(livestock2, initialization_method=\"estimated\").fit()\n",
    "fit2 = Holt(livestock2, initialization_method=\"estimated\").fit()\n",
    "fit3 = Holt(livestock2,exponential=True, initialization_method=\"estimated\").fit()\n",
    "fit4 = Holt(livestock2,damped_trend=True, initialization_method=\"estimated\").fit(damping_trend=0.98)\n",
    "fit5 = Holt(livestock2,exponential=True, damped_trend=True, initialization_method=\"estimated\").fit()\n",
    "params = ['smoothing_level', 'smoothing_trend', 'damping_trend', 'initial_level', 'initial_trend']\n",
    "results=pd.DataFrame(index=[r\"$\\alpha$\",r\"$\\beta$\",r\"$\\phi$\",r\"$l_0$\",\"$b_0$\",\"SSE\"] ,columns=['SES', \"Holt's\",\"Exponential\", \"Additive\", \"Multiplicative\"])\n",
    "results[\"SES\"] =            [fit1.params[p] for p in params] + [fit1.sse]\n",
    "results[\"Holt's\"] =         [fit2.params[p] for p in params] + [fit2.sse]\n",
    "results[\"Exponential\"] =    [fit3.params[p] for p in params] + [fit3.sse]\n",
    "results[\"Additive\"] =       [fit4.params[p] for p in params] + [fit4.sse]\n",
    "results[\"Multiplicative\"] = [fit5.params[p] for p in params] + [fit5.sse]\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plots of Seasonally Adjusted Data\n",
    "The following plots allow us to evaluate the level and slope/trend components of the above table's fits."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:17.105928Z",
     "start_time": "2017-12-07T12:39:16.607306Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Figure 7.4: Level and slope components for Holt’s linear trend method and the additive damped trend method.\n"
     ]
    }
   ],
   "source": [
    "for fit in [fit2,fit4]:\n",
    "    pd.DataFrame(np.c_[fit.level,fit.trend]).rename(\n",
    "        columns={0:'level',1:'slope'}).plot(subplots=True)\n",
    "plt.show()\n",
    "print('Figure 7.4: Level and slope components for Holt’s linear trend method and the additive damped trend method.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparison\n",
    "Here we plot a comparison Simple Exponential Smoothing and Holt's Methods for various additive, exponential and damped combinations. All of the models parameters will be optimized by statsmodels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:18.038995Z",
     "start_time": "2017-12-07T12:39:17.108323Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Figure 7.5: Forecasting livestock, sheep in Asia: comparing forecasting performance of non-seasonal methods.\n"
     ]
    }
   ],
   "source": [
    "fit1 = SimpleExpSmoothing(livestock2, initialization_method=\"estimated\").fit()\n",
    "fcast1 = fit1.forecast(9).rename(\"SES\")\n",
    "fit2 = Holt(livestock2, initialization_method=\"estimated\").fit()\n",
    "fcast2 = fit2.forecast(9).rename(\"Holt's\")\n",
    "fit3 = Holt(livestock2, exponential=True, initialization_method=\"estimated\").fit()\n",
    "fcast3 = fit3.forecast(9).rename(\"Exponential\")\n",
    "fit4 = Holt(livestock2, damped_trend=True, initialization_method=\"estimated\").fit(damping_trend=0.98)\n",
    "fcast4 = fit4.forecast(9).rename(\"Additive Damped\")\n",
    "fit5 = Holt(livestock2, exponential=True, damped_trend=True, initialization_method=\"estimated\").fit()\n",
    "fcast5 = fit5.forecast(9).rename(\"Multiplicative Damped\")\n",
    "\n",
    "ax = livestock2.plot(color=\"black\", marker=\"o\", figsize=(12,8))\n",
    "livestock3.plot(ax=ax, color=\"black\", marker=\"o\", legend=False)\n",
    "fcast1.plot(ax=ax, color='red', legend=True)\n",
    "fcast2.plot(ax=ax, color='green', legend=True)\n",
    "fcast3.plot(ax=ax, color='blue', legend=True)\n",
    "fcast4.plot(ax=ax, color='cyan', legend=True)\n",
    "fcast5.plot(ax=ax, color='magenta', legend=True)\n",
    "ax.set_ylabel('Livestock, sheep in Asia (millions)')\n",
    "plt.show()\n",
    "print('Figure 7.5: Forecasting livestock, sheep in Asia: comparing forecasting performance of non-seasonal methods.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-10-05T09:40:15.958575Z",
     "start_time": "2017-10-05T09:40:15.615Z"
    }
   },
   "source": [
    "## Holt's Winters Seasonal\n",
    "Finally we are able to run full Holt's Winters Seasonal Exponential Smoothing  including a trend component and a seasonal component.\n",
    "statsmodels allows for all the combinations including as shown in the examples below:\n",
    "1. ```fit1``` additive trend, additive seasonal of period ```season_length=4``` and the use of a Box-Cox transformation.\n",
    "1. ```fit2``` additive trend, multiplicative seasonal of period ```season_length=4``` and the use of a Box-Cox transformation..\n",
    "1. ```fit3``` additive damped trend, additive seasonal of period ```season_length=4``` and the use of a Box-Cox transformation.\n",
    "1. ```fit4``` additive damped trend, multiplicative seasonal of period ```season_length=4``` and the use of a Box-Cox transformation.\n",
    "\n",
    "The plot shows the results and forecast for ```fit1``` and ```fit2```.\n",
    "The table allows us to compare the results and parameterizations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:28.375871Z",
     "start_time": "2017-12-07T12:39:18.040674Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Figure 7.6: Forecasting international visitor nights in Australia using Holt-Winters method with both additive and multiplicative seasonality.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Additive</th>\n",
       "      <th>Multiplicative</th>\n",
       "      <th>Additive Dam</th>\n",
       "      <th>Multiplica Dam</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>$\\alpha$</th>\n",
       "      <td>1.490116e-08</td>\n",
       "      <td>1.490116e-08</td>\n",
       "      <td>1.490116e-08</td>\n",
       "      <td>1.490116e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$\\beta$</th>\n",
       "      <td>1.409864e-08</td>\n",
       "      <td>5.533042e-25</td>\n",
       "      <td>6.490738e-09</td>\n",
       "      <td>5.042333e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$\\phi$</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.430416e-01</td>\n",
       "      <td>9.536043e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$\\gamma$</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.388625e-16</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.899280e-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$l_0$</th>\n",
       "      <td>1.119348e+01</td>\n",
       "      <td>1.106373e+01</td>\n",
       "      <td>1.084022e+01</td>\n",
       "      <td>9.899275e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$b_0$</th>\n",
       "      <td>1.205395e-01</td>\n",
       "      <td>1.198953e-01</td>\n",
       "      <td>2.456749e-01</td>\n",
       "      <td>1.975443e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SSE</th>\n",
       "      <td>4.402746e+01</td>\n",
       "      <td>3.611262e+01</td>\n",
       "      <td>3.527619e+01</td>\n",
       "      <td>3.062033e+01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Additive  Multiplicative  Additive Dam  Multiplica Dam\n",
       "$\\alpha$  1.490116e-08    1.490116e-08  1.490116e-08    1.490116e-08\n",
       "$\\beta$   1.409864e-08    5.533042e-25  6.490738e-09    5.042333e-09\n",
       "$\\phi$             NaN             NaN  9.430416e-01    9.536043e-01\n",
       "$\\gamma$  0.000000e+00    5.388625e-16  0.000000e+00    1.899280e-15\n",
       "$l_0$     1.119348e+01    1.106373e+01  1.084022e+01    9.899275e+00\n",
       "$b_0$     1.205395e-01    1.198953e-01  2.456749e-01    1.975443e-01\n",
       "SSE       4.402746e+01    3.611262e+01  3.527619e+01    3.062033e+01"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit1 = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='add', use_boxcox=True, initialization_method=\"estimated\").fit()\n",
    "fit2 = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='mul', use_boxcox=True, initialization_method=\"estimated\").fit()\n",
    "fit3 = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='add', damped_trend=True, use_boxcox=True, initialization_method=\"estimated\").fit()\n",
    "fit4 = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='mul', damped_trend=True, use_boxcox=True, initialization_method=\"estimated\").fit()\n",
    "results=pd.DataFrame(index=[r\"$\\alpha$\",r\"$\\beta$\",r\"$\\phi$\",r\"$\\gamma$\",r\"$l_0$\",\"$b_0$\",\"SSE\"])\n",
    "params = ['smoothing_level', 'smoothing_trend', 'damping_trend', 'smoothing_seasonal', 'initial_level', 'initial_trend']\n",
    "results[\"Additive\"]       = [fit1.params[p] for p in params] + [fit1.sse]\n",
    "results[\"Multiplicative\"] = [fit2.params[p] for p in params] + [fit2.sse]\n",
    "results[\"Additive Dam\"]   = [fit3.params[p] for p in params] + [fit3.sse]\n",
    "results[\"Multiplica Dam\"] = [fit4.params[p] for p in params] + [fit4.sse]\n",
    "\n",
    "ax = aust.plot(figsize=(10,6), marker='o', color='black', title=\"Forecasts from Holt-Winters' multiplicative method\" )\n",
    "ax.set_ylabel(\"International visitor night in Australia (millions)\")\n",
    "ax.set_xlabel(\"Year\")\n",
    "fit1.fittedvalues.plot(ax=ax, style='--', color='red')\n",
    "fit2.fittedvalues.plot(ax=ax, style='--', color='green')\n",
    "\n",
    "fit1.forecast(8).rename('Holt-Winters (add-add-seasonal)').plot(ax=ax, style='--', marker='o', color='red', legend=True)\n",
    "fit2.forecast(8).rename('Holt-Winters (add-mul-seasonal)').plot(ax=ax, style='--', marker='o', color='green', legend=True)\n",
    "\n",
    "plt.show()\n",
    "print(\"Figure 7.6: Forecasting international visitor nights in Australia using Holt-Winters method with both additive and multiplicative seasonality.\")\n",
    "\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Internals\n",
    "It is possible to get at the internals of the Exponential Smoothing models. \n",
    "\n",
    "Here we show some tables that allow you to view side by side the original values $y_t$, the level $l_t$, the trend $b_t$, the season $s_t$ and the fitted values $\\hat{y}_t$. Note that these values only have meaningful values in the space of your original data if the fit is performed without a Box-Cox transformation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "fit1 = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='add', initialization_method=\"estimated\").fit()\n",
    "fit2 = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='mul', initialization_method=\"estimated\").fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:28.399765Z",
     "start_time": "2017-12-07T12:39:28.377215Z"
    }
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>$\\hat{y}_t$</th>\n",
       "      <th>$b_t$</th>\n",
       "      <th>$l_t$</th>\n",
       "      <th>$s_t$</th>\n",
       "      <th>$y_t$</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>44.584128</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>34.297595</td>\n",
       "      <td>10.286532</td>\n",
       "      <td>41.7275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-04-01</th>\n",
       "      <td>24.938189</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>34.895417</td>\n",
       "      <td>-9.957228</td>\n",
       "      <td>24.0418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-07-01</th>\n",
       "      <td>33.005765</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>35.493239</td>\n",
       "      <td>-2.487474</td>\n",
       "      <td>32.3281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-10-01</th>\n",
       "      <td>37.031107</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>36.091061</td>\n",
       "      <td>0.940046</td>\n",
       "      <td>37.3287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-01-01</th>\n",
       "      <td>46.975416</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>36.688883</td>\n",
       "      <td>10.286532</td>\n",
       "      <td>46.2132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-04-01</th>\n",
       "      <td>27.329477</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>37.286705</td>\n",
       "      <td>-9.957228</td>\n",
       "      <td>29.3463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-07-01</th>\n",
       "      <td>35.397053</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>37.884527</td>\n",
       "      <td>-2.487474</td>\n",
       "      <td>36.4829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-01</th>\n",
       "      <td>39.422395</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>38.482349</td>\n",
       "      <td>0.940046</td>\n",
       "      <td>42.9777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-01-01</th>\n",
       "      <td>49.366704</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>39.080171</td>\n",
       "      <td>10.286532</td>\n",
       "      <td>48.9015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-04-01</th>\n",
       "      <td>29.720765</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>39.677993</td>\n",
       "      <td>-9.957228</td>\n",
       "      <td>31.1802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-07-01</th>\n",
       "      <td>37.788341</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>40.275815</td>\n",
       "      <td>-2.487474</td>\n",
       "      <td>37.7179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-10-01</th>\n",
       "      <td>41.813683</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>40.873637</td>\n",
       "      <td>0.940046</td>\n",
       "      <td>40.4202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01</th>\n",
       "      <td>51.757991</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>41.471459</td>\n",
       "      <td>10.286532</td>\n",
       "      <td>51.2069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-01</th>\n",
       "      <td>32.112053</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>42.069281</td>\n",
       "      <td>-9.957228</td>\n",
       "      <td>31.8872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-07-01</th>\n",
       "      <td>40.179629</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>42.667103</td>\n",
       "      <td>-2.487474</td>\n",
       "      <td>40.9783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-10-01</th>\n",
       "      <td>44.204971</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>43.264925</td>\n",
       "      <td>0.940046</td>\n",
       "      <td>43.7725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-01</th>\n",
       "      <td>54.149279</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>43.862747</td>\n",
       "      <td>10.286532</td>\n",
       "      <td>55.5586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-01</th>\n",
       "      <td>34.503341</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>44.460569</td>\n",
       "      <td>-9.957228</td>\n",
       "      <td>33.8509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-07-01</th>\n",
       "      <td>42.570917</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>45.058391</td>\n",
       "      <td>-2.487474</td>\n",
       "      <td>42.0764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-10-01</th>\n",
       "      <td>46.596258</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>45.656213</td>\n",
       "      <td>0.940046</td>\n",
       "      <td>45.6423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>56.540567</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>46.254035</td>\n",
       "      <td>10.286532</td>\n",
       "      <td>59.7668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-04-01</th>\n",
       "      <td>36.894629</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>46.851857</td>\n",
       "      <td>-9.957228</td>\n",
       "      <td>35.1919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-07-01</th>\n",
       "      <td>44.962205</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>47.449679</td>\n",
       "      <td>-2.487474</td>\n",
       "      <td>44.3197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-10-01</th>\n",
       "      <td>48.987546</td>\n",
       "      <td>0.597822</td>\n",
       "      <td>48.047501</td>\n",
       "      <td>0.940046</td>\n",
       "      <td>47.9137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>58.931855</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-01</th>\n",
       "      <td>39.285917</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07-01</th>\n",
       "      <td>47.353493</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10-01</th>\n",
       "      <td>51.378834</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01</th>\n",
       "      <td>61.323143</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-04-01</th>\n",
       "      <td>41.677205</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-07-01</th>\n",
       "      <td>49.744781</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-01</th>\n",
       "      <td>53.770122</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            $\\hat{y}_t$     $b_t$      $l_t$      $s_t$    $y_t$\n",
       "2005-01-01    44.584128  0.597822  34.297595  10.286532  41.7275\n",
       "2005-04-01    24.938189  0.597822  34.895417  -9.957228  24.0418\n",
       "2005-07-01    33.005765  0.597822  35.493239  -2.487474  32.3281\n",
       "2005-10-01    37.031107  0.597822  36.091061   0.940046  37.3287\n",
       "2006-01-01    46.975416  0.597822  36.688883  10.286532  46.2132\n",
       "2006-04-01    27.329477  0.597822  37.286705  -9.957228  29.3463\n",
       "2006-07-01    35.397053  0.597822  37.884527  -2.487474  36.4829\n",
       "2006-10-01    39.422395  0.597822  38.482349   0.940046  42.9777\n",
       "2007-01-01    49.366704  0.597822  39.080171  10.286532  48.9015\n",
       "2007-04-01    29.720765  0.597822  39.677993  -9.957228  31.1802\n",
       "2007-07-01    37.788341  0.597822  40.275815  -2.487474  37.7179\n",
       "2007-10-01    41.813683  0.597822  40.873637   0.940046  40.4202\n",
       "2008-01-01    51.757991  0.597822  41.471459  10.286532  51.2069\n",
       "2008-04-01    32.112053  0.597822  42.069281  -9.957228  31.8872\n",
       "2008-07-01    40.179629  0.597822  42.667103  -2.487474  40.9783\n",
       "2008-10-01    44.204971  0.597822  43.264925   0.940046  43.7725\n",
       "2009-01-01    54.149279  0.597822  43.862747  10.286532  55.5586\n",
       "2009-04-01    34.503341  0.597822  44.460569  -9.957228  33.8509\n",
       "2009-07-01    42.570917  0.597822  45.058391  -2.487474  42.0764\n",
       "2009-10-01    46.596258  0.597822  45.656213   0.940046  45.6423\n",
       "2010-01-01    56.540567  0.597822  46.254035  10.286532  59.7668\n",
       "2010-04-01    36.894629  0.597822  46.851857  -9.957228  35.1919\n",
       "2010-07-01    44.962205  0.597822  47.449679  -2.487474  44.3197\n",
       "2010-10-01    48.987546  0.597822  48.047501   0.940046  47.9137\n",
       "2011-01-01    58.931855       NaN        NaN        NaN      NaN\n",
       "2011-04-01    39.285917       NaN        NaN        NaN      NaN\n",
       "2011-07-01    47.353493       NaN        NaN        NaN      NaN\n",
       "2011-10-01    51.378834       NaN        NaN        NaN      NaN\n",
       "2012-01-01    61.323143       NaN        NaN        NaN      NaN\n",
       "2012-04-01    41.677205       NaN        NaN        NaN      NaN\n",
       "2012-07-01    49.744781       NaN        NaN        NaN      NaN\n",
       "2012-10-01    53.770122       NaN        NaN        NaN      NaN"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.c_[aust, fit1.level, fit1.trend, fit1.season, fit1.fittedvalues],\n",
    "                  columns=[r'$y_t$',r'$l_t$',r'$b_t$',r'$s_t$',r'$\\hat{y}_t$'],index=aust.index)\n",
    "df.append(fit1.forecast(8).rename(r'$\\hat{y}_t$').to_frame(), sort=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:28.574783Z",
     "start_time": "2017-12-07T12:39:28.401234Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>$\\hat{y}_t$</th>\n",
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       "      <th>2005-01-01</th>\n",
       "      <td>43.005390</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>35.016131</td>\n",
       "      <td>1.228159</td>\n",
       "      <td>41.7275</td>\n",
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       "    <tr>\n",
       "      <th>2005-04-01</th>\n",
       "      <td>26.352949</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>35.637067</td>\n",
       "      <td>0.739481</td>\n",
       "      <td>24.0418</td>\n",
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       "    <tr>\n",
       "      <th>2005-07-01</th>\n",
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       "      <td>36.258004</td>\n",
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       "    <tr>\n",
       "      <th>2005-10-01</th>\n",
       "      <td>36.719508</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>36.878940</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>37.3287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-01-01</th>\n",
       "      <td>46.055825</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>37.499877</td>\n",
       "      <td>1.228159</td>\n",
       "      <td>46.2132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-04-01</th>\n",
       "      <td>28.189633</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>38.120813</td>\n",
       "      <td>0.739481</td>\n",
       "      <td>29.3463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-07-01</th>\n",
       "      <td>35.564800</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>38.741750</td>\n",
       "      <td>0.917997</td>\n",
       "      <td>36.4829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-10-01</th>\n",
       "      <td>39.192516</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>39.362686</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>42.9777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-01-01</th>\n",
       "      <td>49.106261</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>39.983623</td>\n",
       "      <td>1.228159</td>\n",
       "      <td>48.9015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-04-01</th>\n",
       "      <td>30.026317</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>40.604559</td>\n",
       "      <td>0.739481</td>\n",
       "      <td>31.1802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-07-01</th>\n",
       "      <td>37.844870</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>41.225496</td>\n",
       "      <td>0.917997</td>\n",
       "      <td>37.7179</td>\n",
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       "    <tr>\n",
       "      <th>2007-10-01</th>\n",
       "      <td>41.665525</td>\n",
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       "      <td>41.846432</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>40.4202</td>\n",
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       "    <tr>\n",
       "      <th>2008-01-01</th>\n",
       "      <td>52.156697</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>42.467369</td>\n",
       "      <td>1.228159</td>\n",
       "      <td>51.2069</td>\n",
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       "    <tr>\n",
       "      <th>2008-04-01</th>\n",
       "      <td>31.863001</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>43.088305</td>\n",
       "      <td>0.739481</td>\n",
       "      <td>31.8872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-07-01</th>\n",
       "      <td>40.124941</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>43.709242</td>\n",
       "      <td>0.917997</td>\n",
       "      <td>40.9783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-10-01</th>\n",
       "      <td>44.138533</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>44.330178</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>43.7725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-01</th>\n",
       "      <td>55.207133</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>44.951115</td>\n",
       "      <td>1.228159</td>\n",
       "      <td>55.5586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-01</th>\n",
       "      <td>33.699685</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>45.572051</td>\n",
       "      <td>0.739481</td>\n",
       "      <td>33.8509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-07-01</th>\n",
       "      <td>42.405012</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>46.192988</td>\n",
       "      <td>0.917997</td>\n",
       "      <td>42.0764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-10-01</th>\n",
       "      <td>46.611542</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>46.813924</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>45.6423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>58.257569</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>47.434861</td>\n",
       "      <td>1.228159</td>\n",
       "      <td>59.7668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-04-01</th>\n",
       "      <td>35.536369</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>48.055797</td>\n",
       "      <td>0.739481</td>\n",
       "      <td>35.1919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-07-01</th>\n",
       "      <td>44.685082</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>48.676733</td>\n",
       "      <td>0.917997</td>\n",
       "      <td>44.3197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-10-01</th>\n",
       "      <td>49.084550</td>\n",
       "      <td>0.620936</td>\n",
       "      <td>49.297670</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>47.9137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>61.308005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-01</th>\n",
       "      <td>37.373053</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07-01</th>\n",
       "      <td>46.965153</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10-01</th>\n",
       "      <td>51.557558</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01</th>\n",
       "      <td>64.358440</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-04-01</th>\n",
       "      <td>39.209737</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-07-01</th>\n",
       "      <td>49.245223</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-01</th>\n",
       "      <td>54.030567</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            $\\hat{y}_t$     $b_t$      $l_t$     $s_t$    $y_t$\n",
       "2005-01-01    43.005390  0.620936  35.016131  1.228159  41.7275\n",
       "2005-04-01    26.352949  0.620936  35.637067  0.739481  24.0418\n",
       "2005-07-01    33.284729  0.620936  36.258004  0.917997  32.3281\n",
       "2005-10-01    36.719508  0.620936  36.878940  0.995677  37.3287\n",
       "2006-01-01    46.055825  0.620936  37.499877  1.228159  46.2132\n",
       "2006-04-01    28.189633  0.620936  38.120813  0.739481  29.3463\n",
       "2006-07-01    35.564800  0.620936  38.741750  0.917997  36.4829\n",
       "2006-10-01    39.192516  0.620936  39.362686  0.995677  42.9777\n",
       "2007-01-01    49.106261  0.620936  39.983623  1.228159  48.9015\n",
       "2007-04-01    30.026317  0.620936  40.604559  0.739481  31.1802\n",
       "2007-07-01    37.844870  0.620936  41.225496  0.917997  37.7179\n",
       "2007-10-01    41.665525  0.620936  41.846432  0.995677  40.4202\n",
       "2008-01-01    52.156697  0.620936  42.467369  1.228159  51.2069\n",
       "2008-04-01    31.863001  0.620936  43.088305  0.739481  31.8872\n",
       "2008-07-01    40.124941  0.620936  43.709242  0.917997  40.9783\n",
       "2008-10-01    44.138533  0.620936  44.330178  0.995677  43.7725\n",
       "2009-01-01    55.207133  0.620936  44.951115  1.228159  55.5586\n",
       "2009-04-01    33.699685  0.620936  45.572051  0.739481  33.8509\n",
       "2009-07-01    42.405012  0.620936  46.192988  0.917997  42.0764\n",
       "2009-10-01    46.611542  0.620936  46.813924  0.995677  45.6423\n",
       "2010-01-01    58.257569  0.620936  47.434861  1.228159  59.7668\n",
       "2010-04-01    35.536369  0.620936  48.055797  0.739481  35.1919\n",
       "2010-07-01    44.685082  0.620936  48.676733  0.917997  44.3197\n",
       "2010-10-01    49.084550  0.620936  49.297670  0.995677  47.9137\n",
       "2011-01-01    61.308005       NaN        NaN       NaN      NaN\n",
       "2011-04-01    37.373053       NaN        NaN       NaN      NaN\n",
       "2011-07-01    46.965153       NaN        NaN       NaN      NaN\n",
       "2011-10-01    51.557558       NaN        NaN       NaN      NaN\n",
       "2012-01-01    64.358440       NaN        NaN       NaN      NaN\n",
       "2012-04-01    39.209737       NaN        NaN       NaN      NaN\n",
       "2012-07-01    49.245223       NaN        NaN       NaN      NaN\n",
       "2012-10-01    54.030567       NaN        NaN       NaN      NaN"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.c_[aust, fit2.level, fit2.trend, fit2.season, fit2.fittedvalues], \n",
    "                  columns=[r'$y_t$',r'$l_t$',r'$b_t$',r'$s_t$',r'$\\hat{y}_t$'],index=aust.index)\n",
    "df.append(fit2.forecast(8).rename(r'$\\hat{y}_t$').to_frame(), sort=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally lets look at the levels, slopes/trends and seasonal components of the models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-12-07T12:39:29.636548Z",
     "start_time": "2017-12-07T12:39:28.576279Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "states1 = pd.DataFrame(np.c_[fit1.level, fit1.trend, fit1.season], columns=['level','slope','seasonal'], index=aust.index)\n",
    "states2 = pd.DataFrame(np.c_[fit2.level, fit2.trend, fit2.season], columns=['level','slope','seasonal'], index=aust.index)\n",
    "fig, [[ax1, ax4],[ax2, ax5], [ax3, ax6]] = plt.subplots(3, 2, figsize=(12,8))\n",
    "states1[['level']].plot(ax=ax1)\n",
    "states1[['slope']].plot(ax=ax2)\n",
    "states1[['seasonal']].plot(ax=ax3)\n",
    "states2[['level']].plot(ax=ax4)\n",
    "states2[['slope']].plot(ax=ax5)\n",
    "states2[['seasonal']].plot(ax=ax6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simulations and Confidence Intervals\n",
    "\n",
    "By using a state space formulation, we can perform simulations of future values. The mathematical details are described in Hyndman and Athanasopoulos [2] and in the documentation of `HoltWintersResults.simulate`.\n",
    "\n",
    "Similar to the example in [2], we use the model with additive trend, multiplicative seasonality, and multiplicative error. We simulate up to 8 steps into the future, and perform 1000 simulations. As can be seen in the below figure, the simulations match the forecast values quite well.\n",
    "\n",
    "[2] [Hyndman, Rob J., and George Athanasopoulos. Forecasting: principles and practice, 2nd edition. OTexts, 2018.](https://otexts.com/fpp2/ets.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fit = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='mul', initialization_method=\"estimated\").fit()\n",
    "simulations = fit.simulate(8, repetitions=100, error='mul')\n",
    "\n",
    "ax = aust.plot(figsize=(10,6), marker='o', color='black', \n",
    "               title=\"Forecasts and simulations from Holt-Winters' multiplicative method\" )\n",
    "ax.set_ylabel(\"International visitor night in Australia (millions)\")\n",
    "ax.set_xlabel(\"Year\")\n",
    "fit.fittedvalues.plot(ax=ax, style='--', color='green')\n",
    "simulations.plot(ax=ax, style='-', alpha=0.05, color='grey', legend=False)\n",
    "fit.forecast(8).rename('Holt-Winters (add-mul-seasonal)').plot(ax=ax, style='--', marker='o', color='green', legend=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Simulations can also be started at different points in time, and there are multiple options for choosing the random noise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fit = ExponentialSmoothing(aust, seasonal_periods=4, trend='add', seasonal='mul', initialization_method=\"estimated\").fit()\n",
    "simulations = fit.simulate(16, anchor='2009-01-01', repetitions=100, error='mul', random_errors='bootstrap')\n",
    "\n",
    "ax = aust.plot(figsize=(10,6), marker='o', color='black', \n",
    "               title=\"Forecasts and simulations from Holt-Winters' multiplicative method\" )\n",
    "ax.set_ylabel(\"International visitor night in Australia (millions)\")\n",
    "ax.set_xlabel(\"Year\")\n",
    "fit.fittedvalues.plot(ax=ax, style='--', color='green')\n",
    "simulations.plot(ax=ax, style='-', alpha=0.05, color='grey', legend=False)\n",
    "fit.forecast(8).rename('Holt-Winters (add-mul-seasonal)').plot(ax=ax, style='--', marker='o', color='green', legend=True)\n",
    "plt.show()"
   ]
  }
 ],
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