MA_Model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1444,
     "status": "ok",
     "timestamp": 1557052945199,
     "user": {
      "displayName": "Bhavesh Bhatt",
      "photoUrl": "https://lh5.googleusercontent.com/-Dxy3HXzth_c/AAAAAAAAAAI/AAAAAAAAHvk/4kcnA5cyAC4/s64/photo.jpg",
      "userId": "01561702845917398436"
     },
     "user_tz": -330
    },
    "id": "-4uF-4X2lj4H",
    "outputId": "756bfa53-a1fe-4155-c06c-06417a2d3b51"
   },
   "outputs": [],
   "source": [
    "from statsmodels.tsa.ar_model import AR\n",
    "from random import random\n",
    "import matplotlib.pyplot as plt\n",
    "from pylab import rcParams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "rcParams['figure.figsize'] = 18, 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "frp5F6vilkrU"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[100.71258486]\n"
     ]
    }
   ],
   "source": [
    "# contrived dataset\n",
    "data = [x + random() for x in range(1, 100)]\n",
    "# fit model\n",
    "model = AR(data)\n",
    "model_fit = model.fit()\n",
    "# make prediction\n",
    "yhat = model_fit.predict(len(data), len(data))\n",
    "print(yhat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 286
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1289,
     "status": "ok",
     "timestamp": 1557052985694,
     "user": {
      "displayName": "Bhavesh Bhatt",
      "photoUrl": "https://lh5.googleusercontent.com/-Dxy3HXzth_c/AAAAAAAAAAI/AAAAAAAAHvk/4kcnA5cyAC4/s64/photo.jpg",
      "userId": "01561702845917398436"
     },
     "user_tz": -330
    },
    "id": "eVIBEIGQlurP",
    "outputId": "386ea4d3-3926-4f82-8b46-313980e1406d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x117b00d30>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 87
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1184,
     "status": "ok",
     "timestamp": 1557053260997,
     "user": {
      "displayName": "Bhavesh Bhatt",
      "photoUrl": "https://lh5.googleusercontent.com/-Dxy3HXzth_c/AAAAAAAAAAI/AAAAAAAAHvk/4kcnA5cyAC4/s64/photo.jpg",
      "userId": "01561702845917398436"
     },
     "user_tz": -330
    },
    "id": "lV-I4fIUlwwC",
    "outputId": "3f1f0878-430f-4fa5-e1ba-8cf7b4500a1d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lag: 12\n",
      "Coefficients: [ 5.29507006e+00  3.72131777e-02  2.62609008e-01  1.22350486e-01\n",
      "  1.93490657e-01  9.74478158e-02 -8.98538515e-02 -7.06844526e-03\n",
      "  2.25296124e-02  5.76491372e-02  3.33768203e-01 -3.24261709e-02\n",
      "  2.78487892e-03]\n"
     ]
    }
   ],
   "source": [
    "print('Lag: %s' % model_fit.k_ar)\n",
    "print('Coefficients: %s' % model_fit.params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1092,
     "status": "ok",
     "timestamp": 1557053358893,
     "user": {
      "displayName": "Bhavesh Bhatt",
      "photoUrl": "https://lh5.googleusercontent.com/-Dxy3HXzth_c/AAAAAAAAAAI/AAAAAAAAHvk/4kcnA5cyAC4/s64/photo.jpg",
      "userId": "01561702845917398436"
     },
     "user_tz": -330
    },
    "id": "FY1Z5cYNl0JT",
    "outputId": "9d2f5a5e-c327-4070-c3ac-f536e408721f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[75.32616828]\n"
     ]
    }
   ],
   "source": [
    "from statsmodels.tsa.arima_model import ARMA\n",
    "from random import random\n",
    "# contrived dataset\n",
    "data = [x + random() for x in range(1, 100)]\n",
    "# fit model\n",
    "model = ARMA(data, order=(0, 1))\n",
    "model_fit = model.fit(disp=False)\n",
    "# make prediction\n",
    "yhat = model_fit.predict(len(data), len(data))\n",
    "print(yhat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 52
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1113,
     "status": "ok",
     "timestamp": 1557053374963,
     "user": {
      "displayName": "Bhavesh Bhatt",
      "photoUrl": "https://lh5.googleusercontent.com/-Dxy3HXzth_c/AAAAAAAAAAI/AAAAAAAAHvk/4kcnA5cyAC4/s64/photo.jpg",
      "userId": "01561702845917398436"
     },
     "user_tz": -330
    },
    "id": "6hV16vlknL58",
    "outputId": "6f873472-2156-41de-956a-2b70afaa6889"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lag: 0\n",
      "Coefficients: [50.4646432  0.9999669]\n"
     ]
    }
   ],
   "source": [
    "print('Lag: %s' % model_fit.k_ar)\n",
    "print('Coefficients: %s' % model_fit.params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1208,
     "status": "ok",
     "timestamp": 1558240279561,
     "user": {
      "displayName": "Bhavesh Bhatt",
      "photoUrl": "https://lh5.googleusercontent.com/-Dxy3HXzth_c/AAAAAAAAAAI/AAAAAAAAHvk/4kcnA5cyAC4/s64/photo.jpg",
      "userId": "01561702845917398436"
     },
     "user_tz": -330
    },
    "id": "5TzJAP4UnPzk",
    "outputId": "fe40fa95-efc8-4833-947f-0196291e2f1d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10.31049871  9.29724208 10.69207454 10.19993954 11.36646044 10.68586874]\n"
     ]
    }
   ],
   "source": [
    "from statsmodels.tsa.arima_model import ARMA\n",
    "from random import random\n",
    "# contrived dataset\n",
    "# data = [10, 9, 10.5, 10, 11]\n",
    "data = [8, 10, 10.5, 12, 12]\n",
    "# fit model\n",
    "model = ARMA(data, order=(0, 1))\n",
    "model_fit = model.fit(disp=False)\n",
    "# make prediction\n",
    "yhat = model_fit.predict(0, len(data))\n",
    "print(yhat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 286
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1257,
     "status": "ok",
     "timestamp": 1558240865357,
     "user": {
      "displayName": "Bhavesh Bhatt",
      "photoUrl": "https://lh5.googleusercontent.com/-Dxy3HXzth_c/AAAAAAAAAAI/AAAAAAAAHvk/4kcnA5cyAC4/s64/photo.jpg",
      "userId": "01561702845917398436"
     },
     "user_tz": -330
    },
    "id": "aMLeat0ZXgFL",
    "outputId": "1102a85f-43fc-4b9d-c6dc-827b32c1817f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x11823a940>]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(data)\n",
    "plt.plot(model_fit.predict(0, len(data)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1192,
     "status": "ok",
     "timestamp": 1558240294373,
     "user": {
      "displayName": "Bhavesh Bhatt",
      "photoUrl": "https://lh5.googleusercontent.com/-Dxy3HXzth_c/AAAAAAAAAAI/AAAAAAAAHvk/4kcnA5cyAC4/s64/photo.jpg",
      "userId": "01561702845917398436"
     },
     "user_tz": -330
    },
    "id": "y7o_RZm1oOEC",
    "outputId": "fd428222-7629-4117-a011-a02333b4f626"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lag: 0\n",
      "Coefficients: [10.31049871  0.59249659]\n"
     ]
    }
   ],
   "source": [
    "print('Lag: %s' % model_fit.k_ar)\n",
    "print('Coefficients: %s' % model_fit.params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "eBfUuQjAWqvg"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1182ab358>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(data)\n",
    "plt.plot(model_fit.predict(0, len(data)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 52
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 956,
     "status": "ok",
     "timestamp": 1557055550968,
     "user": {
      "displayName": "Bhavesh Bhatt",
      "photoUrl": "https://lh5.googleusercontent.com/-Dxy3HXzth_c/AAAAAAAAAAI/AAAAAAAAHvk/4kcnA5cyAC4/s64/photo.jpg",
      "userId": "01561702845917398436"
     },
     "user_tz": -330
    },
    "id": "CVerTfUHnbUT",
    "outputId": "555028cb-047a-4f3b-9786-37c1db0344c4"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lag: 0\n",
      "Coefficients: [10.31049871  0.59249659]\n"
     ]
    }
   ],
   "source": [
    "print('Lag: %s' % model_fit.k_ar)\n",
    "print('Coefficients: %s' % model_fit.params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 286
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1306,
     "status": "ok",
     "timestamp": 1557055642502,
     "user": {
      "displayName": "Bhavesh Bhatt",
      "photoUrl": "https://lh5.googleusercontent.com/-Dxy3HXzth_c/AAAAAAAAAAI/AAAAAAAAHvk/4kcnA5cyAC4/s64/photo.jpg",
      "userId": "01561702845917398436"
     },
     "user_tz": -330
    },
    "id": "IEmszxgnndZl",
    "outputId": "c7ab73ed-b039-483b-87a8-854a30698c90"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1185f87b8>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(data)\n",
    "plt.plot(model_fit.predict(0, len(data)))"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "name": "MA_Model.ipynb",
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