15_theta.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a24421d1",
   "metadata": {},
   "source": [
    "# Theta model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "65c5226b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "419acc7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams[\"figure.figsize\"] = (9,6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a4a81c6e",
   "metadata": {},
   "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>co2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1958-03-29</th>\n",
       "      <td>316.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-04-05</th>\n",
       "      <td>317.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-04-12</th>\n",
       "      <td>317.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-04-19</th>\n",
       "      <td>317.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-04-26</th>\n",
       "      <td>316.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              co2\n",
       "1958-03-29  316.1\n",
       "1958-04-05  317.3\n",
       "1958-04-12  317.6\n",
       "1958-04-19  317.5\n",
       "1958-04-26  316.4"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = sm.datasets.co2.load_pandas().data\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "dc50336f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.plot(df['co2'])\n",
    "ax.set_xlabel('Time')\n",
    "ax.set_ylabel('CO2 concentration (ppmw)')\n",
    "\n",
    "fig.autofmt_xdate()\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "33c7bd00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "co2    59\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "080dd290",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "co2    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.interpolate()\n",
    "\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a2b2da04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.plot(df['co2'])\n",
    "ax.set_xlabel('Time')\n",
    "ax.set_ylabel('CO2 concentration (ppmw)')\n",
    "\n",
    "fig.autofmt_xdate()\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c501b13",
   "metadata": {},
   "source": [
    "## Modeling "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "53b54b32",
   "metadata": {},
   "outputs": [],
   "source": [
    "train = df[:-104]\n",
    "test = df[-104:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "19864972",
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tsa.forecasting.theta import ThetaModel\n",
    "\n",
    "def rolling_forecast(df: pd.DataFrame, train_len: int, horizon: int, window: int, period: int, method: str) -> list:\n",
    "    \n",
    "    seasonal_steps = int((window/period))\n",
    "    \n",
    "    TOTAL_LEN = train_len + horizon\n",
    "\n",
    "    if method == 'last_season':\n",
    "        pred_last_season = []\n",
    "        \n",
    "        for i in range(train_len, TOTAL_LEN, window):\n",
    "            last_season = df[:i][-period:].values\n",
    "            pred_last_season.extend(last_season for _ in range(seasonal_steps))\n",
    "\n",
    "        pred_last_season = np.array(pred_last_season).reshape(1, -1)\n",
    "        \n",
    "        return pred_last_season[0][:horizon]\n",
    "    \n",
    "    elif method == 'theta':\n",
    "        pred_theta = []\n",
    "        \n",
    "        for i in range(train_len, TOTAL_LEN, window):\n",
    "            tm = ThetaModel(endog=df[:i], period=52)\n",
    "            res = tm.fit()\n",
    "            predictions = res.forecast(window)\n",
    "            pred_theta.extend(predictions)\n",
    "            \n",
    "        print(res.summary())\n",
    "\n",
    "        return pred_theta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "57f6667b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                              ThetaModel Results                              \n",
      "==============================================================================\n",
      "Dep. Variable:                    co2   No. Observations:                 2232\n",
      "Method:                       OLS/SES   Deseasonalized:                   True\n",
      "Date:                Sun, 08 Jan 2023   Deseas. Method:         Multiplicative\n",
      "Time:                        17:11:18   Period:                             52\n",
      "Sample:                    03-29-1958                                         \n",
      "                         - 12-30-2000                                         \n",
      "   Parameter Estimates    \n",
      "==========================\n",
      "           Parameters     \n",
      "--------------------------\n",
      "b0    0.025468131021064107\n",
      "alpha   0.6611560971437324\n",
      "--------------------------\n"
     ]
    },
    {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>co2</th>\n",
       "      <th>pred_last_season</th>\n",
       "      <th>pred_theta</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-08</th>\n",
       "      <td>368.5</td>\n",
       "      <td>367.8</td>\n",
       "      <td>368.688671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-15</th>\n",
       "      <td>369.0</td>\n",
       "      <td>367.8</td>\n",
       "      <td>368.791990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-22</th>\n",
       "      <td>369.8</td>\n",
       "      <td>368.3</td>\n",
       "      <td>368.986970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-29</th>\n",
       "      <td>369.2</td>\n",
       "      <td>369.2</td>\n",
       "      <td>369.111453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-05</th>\n",
       "      <td>369.1</td>\n",
       "      <td>369.1</td>\n",
       "      <td>369.424445</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              co2  pred_last_season  pred_theta\n",
       "2000-01-08  368.5             367.8  368.688671\n",
       "2000-01-15  369.0             367.8  368.791990\n",
       "2000-01-22  369.8             368.3  368.986970\n",
       "2000-01-29  369.2             369.2  369.111453\n",
       "2000-02-05  369.1             369.1  369.424445"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TRAIN_LEN = len(train)\n",
    "HORIZON = len(test)\n",
    "PERIOD = 52\n",
    "WINDOW = 52\n",
    "\n",
    "pred_last_season = rolling_forecast(df, TRAIN_LEN, HORIZON, WINDOW, PERIOD, 'last_season')\n",
    "pred_theta = rolling_forecast(df, TRAIN_LEN, HORIZON, WINDOW, PERIOD, 'theta')\n",
    "\n",
    "test = test.copy()\n",
    "\n",
    "test.loc[:, 'pred_last_season'] = pred_last_season\n",
    "test.loc[:, 'pred_theta'] = pred_theta\n",
    "\n",
    "test.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0139d13e",
   "metadata": {},
   "source": [
    "## Testing triple exponential smoothing "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "c8c9332b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tsa.holtwinters import ExponentialSmoothing\n",
    "\n",
    "def rolling_forecast(df: pd.DataFrame, train_len: int, horizon: int, window: int, period: int, method: str) -> list:\n",
    "    \n",
    "    seasonal_steps = int((window/period))\n",
    "    \n",
    "    TOTAL_LEN = train_len + horizon\n",
    "\n",
    "    if method == 'last_season':\n",
    "        pred_last_season = []\n",
    "        \n",
    "        for i in range(train_len, TOTAL_LEN, window):\n",
    "            last_season = df[:i][-period:].values\n",
    "            pred_last_season.extend(last_season for _ in range(seasonal_steps))\n",
    "\n",
    "        pred_last_season = np.array(pred_last_season).reshape(1, -1)\n",
    "        \n",
    "        return pred_last_season[0][:horizon]\n",
    "    \n",
    "    elif method == 'theta':\n",
    "        pred_theta = []\n",
    "        \n",
    "        for i in range(train_len, TOTAL_LEN, window):\n",
    "            tm = ThetaModel(endog=df[:i], period=52)\n",
    "            res = tm.fit()\n",
    "            predictions = res.forecast(window)\n",
    "            pred_theta.extend(predictions)\n",
    "            \n",
    "\n",
    "        return pred_theta\n",
    "            \n",
    "    elif method == 'tes':\n",
    "        pred_tes = []\n",
    "        \n",
    "        for i in range(train_len, TOTAL_LEN, window):\n",
    "            tes = ExponentialSmoothing(\n",
    "                df[:i],\n",
    "                trend='add',\n",
    "                seasonal='add',\n",
    "                seasonal_periods=52,\n",
    "                initialization_method='estimated'\n",
    "            ).fit()\n",
    "            \n",
    "            predictions = tes.forecast(window)\n",
    "            pred_tes.extend(predictions)\n",
    "\n",
    "        return pred_tes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "121bfae9",
   "metadata": {},
   "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>co2</th>\n",
       "      <th>pred_last_season</th>\n",
       "      <th>pred_theta</th>\n",
       "      <th>pred_tes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-08</th>\n",
       "      <td>368.5</td>\n",
       "      <td>367.8</td>\n",
       "      <td>368.688671</td>\n",
       "      <td>368.923702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-15</th>\n",
       "      <td>369.0</td>\n",
       "      <td>367.8</td>\n",
       "      <td>368.791990</td>\n",
       "      <td>368.947825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-22</th>\n",
       "      <td>369.8</td>\n",
       "      <td>368.3</td>\n",
       "      <td>368.986970</td>\n",
       "      <td>369.229236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-29</th>\n",
       "      <td>369.2</td>\n",
       "      <td>369.2</td>\n",
       "      <td>369.111453</td>\n",
       "      <td>369.630765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-05</th>\n",
       "      <td>369.1</td>\n",
       "      <td>369.1</td>\n",
       "      <td>369.424445</td>\n",
       "      <td>369.881109</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              co2  pred_last_season  pred_theta    pred_tes\n",
       "2000-01-08  368.5             367.8  368.688671  368.923702\n",
       "2000-01-15  369.0             367.8  368.791990  368.947825\n",
       "2000-01-22  369.8             368.3  368.986970  369.229236\n",
       "2000-01-29  369.2             369.2  369.111453  369.630765\n",
       "2000-02-05  369.1             369.1  369.424445  369.881109"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_tes = rolling_forecast(df, TRAIN_LEN, HORIZON, WINDOW, PERIOD, 'tes')\n",
    "\n",
    "test.loc[:, 'pred_tes'] = pred_tes\n",
    "\n",
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0a1af69f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.plot(df['co2'])\n",
    "ax.plot(test['co2'], 'b-', label='actual')\n",
    "ax.plot(test['pred_last_season'], 'r:', label='baseline')\n",
    "ax.plot(test['pred_theta'], 'g-.', label='Theta')\n",
    "ax.plot(test['pred_tes'], 'k--', label='TES')\n",
    "\n",
    "ax.set_xlabel('Time')\n",
    "ax.set_ylabel('CO2 concentration (ppmv)')\n",
    "ax.axvspan('2000-01-08', '2001-12-29', color='#808080', alpha=0.2)\n",
    "\n",
    "ax.legend(loc='best')\n",
    "\n",
    "ax.set_xlim('1998-03-07', '2001-12-29')\n",
    "\n",
    "fig.autofmt_xdate()\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b03a6c5a",
   "metadata": {},
   "source": [
    "## Evaluation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "22aac8a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def mape(y_true, y_pred):\n",
    "    return round(np.mean(np.abs((y_true - y_pred) / y_true)) * 100, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ef22a629",
   "metadata": {},
   "outputs": [],
   "source": [
    "mape_baseline = mape(test['co2'], test['pred_last_season'])\n",
    "mape_theta = mape(test['co2'], test['pred_theta'])\n",
    "mape_tes = mape(test['co2'], test['pred_tes'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "2d9831bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "x = ['Baseline', 'Theta', 'TES']\n",
    "y = [mape_baseline, mape_theta, mape_tes]\n",
    "\n",
    "ax.bar(x, y, width=0.4)\n",
    "ax.set_xlabel('Exponential smoothing models')\n",
    "ax.set_ylabel('MAPE (%)')\n",
    "ax.set_ylim(0, 1)\n",
    "\n",
    "for index, value in enumerate(y):\n",
    "    plt.text(x=index, y=value + 0.05, s=str(value), ha='center')\n",
    "    \n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5250a371",
   "metadata": {},
   "source": [
    "## Testing SARIMA "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "1d1f718c",
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.stats.diagnostic import acorr_ljungbox\n",
    "from statsmodels.tsa.statespace.sarimax import SARIMAX\n",
    "from statsmodels.tsa.stattools import adfuller\n",
    "from tqdm import tqdm_notebook\n",
    "from itertools import product"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9cad2d44",
   "metadata": {},
   "source": [
    "### Test for stationarity "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "9eeb4617",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ADF Statistic: 0.03378459745825743\n",
      "p-value: 0.9612384528286101\n"
     ]
    }
   ],
   "source": [
    "ad_fuller_result = adfuller(df['co2'])\n",
    "\n",
    "print(f'ADF Statistic: {ad_fuller_result[0]}')\n",
    "print(f'p-value: {ad_fuller_result[1]}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "19a2414f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ADF Statistic: -15.727522408375824\n",
      "p-value: 1.3013480157810985e-28\n"
     ]
    }
   ],
   "source": [
    "df_diff = np.diff(df['co2'], n=1)\n",
    "\n",
    "ad_fuller_result = adfuller(df_diff)\n",
    "\n",
    "print(f'ADF Statistic: {ad_fuller_result[0]}')\n",
    "print(f'p-value: {ad_fuller_result[1]}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "56c4648f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def SARIMA_gridsearch(endog, min_p, max_p, min_q, max_q, min_P, max_P, min_Q, max_Q, d, D, s):\n",
    "    \n",
    "    all_p = range(min_p, max_p+1, 1)\n",
    "    all_q = range(min_q, max_q+1, 1)\n",
    "    all_P = range(min_P, max_P+1, 1)\n",
    "    all_Q = range(min_Q, max_Q+1, 1)\n",
    "    \n",
    "    all_orders = list(product(all_p, all_q, all_P, all_Q))\n",
    "    \n",
    "    print(f'Fitting {len(all_orders)} unique models')\n",
    "    \n",
    "    results = []\n",
    "    \n",
    "    for order in tqdm_notebook(all_orders):\n",
    "        try: \n",
    "            model = SARIMAX(\n",
    "                endog, \n",
    "                order=(order[0], d, order[1]),\n",
    "                seasonal_order=(order[2], D, order[3], s)).fit(disp=False)\n",
    "        except:\n",
    "            continue\n",
    "            \n",
    "        results.append([order, model.aic])\n",
    "        \n",
    "    result_df = pd.DataFrame(results)\n",
    "    result_df.columns = ['(p,q,P,Q)', 'AIC']\n",
    "    \n",
    "    #Sort in ascending order, lower AIC is better\n",
    "    result_df = result_df.sort_values(by='AIC', ascending=True).reset_index(drop=True)\n",
    "    \n",
    "    return result_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "43298bb1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 9 unique models\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:14: TqdmDeprecationWarning: This function will be removed in tqdm==5.0.0\n",
      "Please use `tqdm.notebook.tqdm` instead of `tqdm.tqdm_notebook`\n",
      "  \n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "314ce069d28449fbbf277c6dce19cad6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/9 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\statsmodels\\tsa\\statespace\\sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n",
      "  warn('Non-stationary starting autoregressive parameters'\n",
      "D:\\Anaconda3\\lib\\site-packages\\statsmodels\\tsa\\statespace\\sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n",
      "  warn('Non-invertible starting MA parameters found.'\n",
      "D:\\Anaconda3\\lib\\site-packages\\statsmodels\\base\\model.py:606: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  ConvergenceWarning)\n",
      "D:\\Anaconda3\\lib\\site-packages\\statsmodels\\base\\model.py:606: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  ConvergenceWarning)\n",
      "D:\\Anaconda3\\lib\\site-packages\\statsmodels\\base\\model.py:606: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  ConvergenceWarning)\n",
      "D:\\Anaconda3\\lib\\site-packages\\statsmodels\\base\\model.py:606: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  ConvergenceWarning)\n",
      "D:\\Anaconda3\\lib\\site-packages\\statsmodels\\base\\model.py:606: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  ConvergenceWarning)\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>(p,q,P,Q)</th>\n",
       "      <th>AIC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(2, 3, 1, 1)</td>\n",
       "      <td>2082.620248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(3, 3, 1, 1)</td>\n",
       "      <td>2084.881691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(3, 2, 1, 1)</td>\n",
       "      <td>2085.756333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(3, 1, 1, 1)</td>\n",
       "      <td>2090.990804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(1, 3, 1, 1)</td>\n",
       "      <td>2097.624660</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      (p,q,P,Q)          AIC\n",
       "0  (2, 3, 1, 1)  2082.620248\n",
       "1  (3, 3, 1, 1)  2084.881691\n",
       "2  (3, 2, 1, 1)  2085.756333\n",
       "3  (3, 1, 1, 1)  2090.990804\n",
       "4  (1, 3, 1, 1)  2097.624660"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min_p = 1\n",
    "max_p = 3\n",
    "min_q = 1\n",
    "max_q = 3\n",
    "\n",
    "min_P = 1\n",
    "max_P = 1\n",
    "min_Q = 1\n",
    "max_Q = 1\n",
    "\n",
    "d = 1\n",
    "D = 0\n",
    "s = 52\n",
    "\n",
    "result_df = SARIMA_gridsearch(train, min_p, max_p, min_q, max_q, min_P, max_P, min_Q, max_Q, d, D, s)\n",
    "result_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "7ee5c8e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\statsmodels\\base\\model.py:606: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  ConvergenceWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                      SARIMAX Results                                       \n",
      "============================================================================================\n",
      "Dep. Variable:                                  co2   No. Observations:                 2180\n",
      "Model:             SARIMAX(2, 1, 3)x(1, 0, [1], 52)   Log Likelihood               -1033.310\n",
      "Date:                              Sun, 08 Jan 2023   AIC                           2082.620\n",
      "Time:                                      17:18:07   BIC                           2128.113\n",
      "Sample:                                  03-29-1958   HQIC                          2099.252\n",
      "                                       - 01-01-2000                                         \n",
      "Covariance Type:                       Not computed                                         \n",
      "==============================================================================\n",
      "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "ar.L1          0.4328        nan        nan        nan         nan         nan\n",
      "ar.L2          0.4608        nan        nan        nan         nan         nan\n",
      "ma.L1         -0.8645        nan        nan        nan         nan         nan\n",
      "ma.L2         -0.4643        nan        nan        nan         nan         nan\n",
      "ma.L3          0.3480        nan        nan        nan         nan         nan\n",
      "ar.S.L52       0.9943        nan        nan        nan         nan         nan\n",
      "ma.S.L52      -0.8336        nan        nan        nan         nan         nan\n",
      "sigma2         0.1436        nan        nan        nan         nan         nan\n",
      "===================================================================================\n",
      "Ljung-Box (L1) (Q):                   0.06   Jarque-Bera (JB):               108.07\n",
      "Prob(Q):                              0.81   Prob(JB):                         0.00\n",
      "Heteroskedasticity (H):               1.23   Skew:                            -0.25\n",
      "Prob(H) (two-sided):                  0.01   Kurtosis:                         3.97\n",
      "===================================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Covariance matrix not calculated.\n"
     ]
    }
   ],
   "source": [
    "SARIMA_model = SARIMAX(train, order=(2,1,3), seasonal_order=(1,0,1,52), simple_differencing=False)\n",
    "SARIMA_model_fit = SARIMA_model.fit(cov_type='none')\n",
    "\n",
    "print(SARIMA_model_fit.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "c193cef8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SARIMA_model_fit.plot_diagnostics();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "17eccb2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def ljung_box_test(residuals, is_seasonal, period):\n",
    "    \n",
    "    if is_seasonal:\n",
    "        lb_df = acorr_ljungbox(residuals, period=period)\n",
    "    else:\n",
    "        max_lag = min([10, len(residuals)/5])\n",
    "        \n",
    "        lb_df = acorr_ljungbox(residuals, np.arange(1, max_lag+1, 1))\n",
    "\n",
    "    fig, ax = plt.subplots()\n",
    "    ax.plot(lb_df['lb_pvalue'], 'b-', label='p-values')\n",
    "    ax.hlines(y=0.05, xmin=1, xmax=len(lb_df), color='black')\n",
    "    plt.tight_layout()\n",
    "    \n",
    "    if all(pvalue > 0.05 for pvalue in lb_df['lb_pvalue']):\n",
    "        print('All values are above 0.05. We fail to reject the null hypothesis. The residuals are uncorrelated')\n",
    "    else:\n",
    "        print('At least one p-value is smaller than 0.05')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "a8973ee5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "All values are above 0.05. We fail to reject the null hypothesis. The residuals are uncorrelated\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "residuals = SARIMA_model_fit.resid\n",
    "\n",
    "ljung_box_test(residuals, True, 52)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "3d95c7d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tsa.holtwinters import ExponentialSmoothing\n",
    "\n",
    "def rolling_forecast(df: pd.DataFrame, train_len: int, horizon: int, window: int, period: int, method: str) -> list:\n",
    "    \n",
    "    seasonal_steps = int((window/period))\n",
    "    \n",
    "    TOTAL_LEN = train_len + horizon\n",
    "\n",
    "    if method == 'last_season':\n",
    "        pred_last_season = []\n",
    "        \n",
    "        for i in range(train_len, TOTAL_LEN, window):\n",
    "            last_season = df[:i][-period:].values\n",
    "            pred_last_season.extend(last_season for _ in range(seasonal_steps))\n",
    "\n",
    "        pred_last_season = np.array(pred_last_season).reshape(1, -1)\n",
    "        \n",
    "        return pred_last_season[0][:horizon]\n",
    "    \n",
    "    elif method == 'theta':\n",
    "        pred_theta = []\n",
    "        \n",
    "        for i in range(train_len, total_len, window):\n",
    "            tm = ThetaModel(endog=df[:i], period=52)\n",
    "            res = tm.fit()\n",
    "            predictions = res.forecast(window)\n",
    "            pred_theta.extend(predictions)\n",
    "            \n",
    "\n",
    "        return pred_theta\n",
    "            \n",
    "    elif method == 'tes':\n",
    "        pred_tes = []\n",
    "        \n",
    "        for i in range(train_len, total_len, window):\n",
    "            tes = ExponentialSmoothing(\n",
    "                df[:i],\n",
    "                trend='add',\n",
    "                seasonal='add',\n",
    "                seasonal_periods=52,\n",
    "                initialization_method='estimated'\n",
    "            ).fit()\n",
    "            \n",
    "            predictions = tes.forecast(window)\n",
    "            pred_tes.extend(predictions)\n",
    "\n",
    "        return pred_tes\n",
    "\n",
    "    elif method == 'SARIMA':\n",
    "        pred_SARIMA = []\n",
    "        \n",
    "        for i in range(train_len, TOTAL_LEN, window):\n",
    "            model = SARIMAX(df[:i], order=(2,1,3), seasonal_order=(1,0,2,52))\n",
    "            res = model.fit(cov_type='none')\n",
    "            predictions = res.get_prediction(0, i + window - 1)\n",
    "            oos_pred = predictions.predicted_mean.iloc[-window:]\n",
    "            pred_SARIMA.extend(oos_pred)\n",
    "            \n",
    "        return pred_SARIMA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "047fec03",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\statsmodels\\base\\model.py:606: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  ConvergenceWarning)\n",
      "D:\\Anaconda3\\lib\\site-packages\\statsmodels\\base\\model.py:606: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  ConvergenceWarning)\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>co2</th>\n",
       "      <th>pred_last_season</th>\n",
       "      <th>pred_theta</th>\n",
       "      <th>pred_tes</th>\n",
       "      <th>pred_SARIMA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-08</th>\n",
       "      <td>368.5</td>\n",
       "      <td>367.8</td>\n",
       "      <td>368.688671</td>\n",
       "      <td>368.923702</td>\n",
       "      <td>368.772869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-15</th>\n",
       "      <td>369.0</td>\n",
       "      <td>367.8</td>\n",
       "      <td>368.791990</td>\n",
       "      <td>368.947825</td>\n",
       "      <td>368.823850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-22</th>\n",
       "      <td>369.8</td>\n",
       "      <td>368.3</td>\n",
       "      <td>368.986970</td>\n",
       "      <td>369.229236</td>\n",
       "      <td>369.023440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-29</th>\n",
       "      <td>369.2</td>\n",
       "      <td>369.2</td>\n",
       "      <td>369.111453</td>\n",
       "      <td>369.630765</td>\n",
       "      <td>369.223036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-02-05</th>\n",
       "      <td>369.1</td>\n",
       "      <td>369.1</td>\n",
       "      <td>369.424445</td>\n",
       "      <td>369.881109</td>\n",
       "      <td>369.683877</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              co2  pred_last_season  pred_theta    pred_tes  pred_SARIMA\n",
       "2000-01-08  368.5             367.8  368.688671  368.923702   368.772869\n",
       "2000-01-15  369.0             367.8  368.791990  368.947825   368.823850\n",
       "2000-01-22  369.8             368.3  368.986970  369.229236   369.023440\n",
       "2000-01-29  369.2             369.2  369.111453  369.630765   369.223036\n",
       "2000-02-05  369.1             369.1  369.424445  369.881109   369.683877"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_SARIMA = rolling_forecast(df, TRAIN_LEN, HORIZON, WINDOW, PERIOD, 'SARIMA')\n",
    "\n",
    "test.loc[:, 'pred_SARIMA'] = pred_SARIMA\n",
    "\n",
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "132d3daa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.plot(df['co2'])\n",
    "ax.plot(test['co2'], 'b-', label='actual')\n",
    "ax.plot(test['pred_last_season'], 'r:', label='baseline')\n",
    "ax.plot(test['pred_theta'], 'g-.', label='Theta')\n",
    "ax.plot(test['pred_tes'], 'k--', label='TES')\n",
    "ax.plot(test['pred_SARIMA'], label='SARIMA')\n",
    "\n",
    "ax.set_xlabel('Time')\n",
    "ax.set_ylabel('CO2 concentration (ppmv)')\n",
    "ax.axvspan('2000-01-08', '2001-12-29', color='#808080', alpha=0.2)\n",
    "\n",
    "ax.legend(loc='best')\n",
    "\n",
    "ax.set_xlim('1998-03-07', '2001-12-29')\n",
    "\n",
    "fig.autofmt_xdate()\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "259f23d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "mape_SARIMA = mape(test['co2'], test['pred_SARIMA'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "8fbe1d85",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "x = ['Baseline', 'Theta', 'TES', 'SARIMA']\n",
    "y = [mape_baseline, mape_theta, mape_tes, mape_SARIMA]\n",
    "\n",
    "ax.bar(x, y, width=0.4)\n",
    "ax.set_xlabel('Exponential smoothing models')\n",
    "ax.set_ylabel('MAPE (%)')\n",
    "ax.set_ylim(0, 1)\n",
    "\n",
    "for index, value in enumerate(y):\n",
    "    plt.text(x=index, y=value + 0.05, s=str(value), ha='center')\n",
    "    \n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15bfa4ad",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}