LDHRserieIPI.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# IPI y valor añadido de la industria"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para el filtrado (filtro de Kalman y suavizado de intervalo fijo) usaremos la toolbok [E4](https://www.ucm.es/e-4/), para ello es necesario ejecutar lo siguiente:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "            XXXXXX 4 4      XXXXX  XX     XX  XX  XXXXXX (c)\r\n",
      "           XX      444     XX  XX XX     XX  XX  XX\r\n",
      "          XXXX       4    XXXXX  XX     XX  XX  XXXXXX\r\n",
      "         XX              XX     XX     XX  XX      XX\r\n",
      "        XXXXXX          XX     XXXXXX XXXXXX  XXXXXX\r\n",
      "\r\n",
      "    Toolbox for State Space Estimation of Econometric Models\r\n",
      " \r\n",
      "*********************** Options set by user ********************\r\n",
      "Filter. . . . . . . . . . . . . : KALMAN\r\n",
      "Scaled B and M matrices . . . . : NO\r\n",
      "Initial state vector. . . . . . : AUTOMATIC SELECTION\r\n",
      "Initial covariance of state v.  : IDEJONG\r\n",
      "Variance or Cholesky factor?  . : VARIANCE\r\n",
      "Optimization algorithm. . . . . : BFGS\r\n",
      "Maximum step length . . . . . . : 0.100000\r\n",
      "Stop tolerance. . . . . . . . . : 0.000010\r\n",
      "Max. number of iterations . . . :       75\r\n",
      "Verbose iterations. . . . . . . : YES\r\n",
      "****************************************************************\r\n",
      " \r\n",
      " \r\n"
     ]
    }
   ],
   "source": [
    "e4init\n",
    "figure(1); close(1) # en mi PC me da error al generar las figuras png embedidas en el notebook si no hago esto."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tambien es necesario cargar el toolbox de control"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pkg load control"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cargamos los datos de la serie _\"ipi\"_ y la transformamos con `log`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "load data/ipi.txt\n",
    "log_ipi=log(ipi);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%plot --format png\n",
    "plot(log_ipi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PaP =\n",
      "\n",
      "       Inf   12.0000    6.0000    4.0000    3.0000    2.4000    2.0000\n",
      "\n",
      "TVPaP =\n",
      "\n",
      "   1   1   1   1   1   1   1\n",
      "   1   0   0   0   0   0   0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "filt=0;\n",
    "PaP=12./(0:6)\n",
    "TVPaP=[1 1 1 1 1 1 1;1 0 0 0 0 0 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VAR =\r\n",
      "\r\n",
      " Columns 1 through 6:\r\n",
      "\r\n",
      "   4.1801e-04   2.1030e-06   3.4163e-06   1.0080e-06   4.6124e-06   1.1629e-05\r\n",
      "\r\n",
      " Columns 7 and 8:\r\n",
      "\r\n",
      "   6.5676e-06   4.7243e-06\r\n",
      "\r\n",
      "P =\r\n",
      "\r\n",
      "       Inf   12.0000    6.0000    4.0000    3.0000    2.4000    2.0000\r\n",
      "\r\n",
      "TVP =\r\n",
      "\r\n",
      "   1.0000   1.0000   1.0000   1.0000   1.0000   1.0000   1.0000\r\n",
      "   0.9255        0        0        0        0        0        0\r\n",
      "\r\n",
      "oar = 17\r\n"
     ]
    }
   ],
   "source": [
    "[VAR,P,TVP,oar]=autodhr(log_ipi,12,[],[],PaP,TVPaP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NVR =\r\n",
      "\r\n",
      " Columns 1 through 6:\r\n",
      "\r\n",
      "   5.0311e-03   8.1728e-03   2.4115e-03   1.1034e-02   2.7821e-02   1.5712e-02\r\n",
      "\r\n",
      " Column 7:\r\n",
      "\r\n",
      "   1.1302e-02\r\n",
      "\r\n"
     ]
    }
   ],
   "source": [
    "NVR=VAR(2:8)./VAR(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "[trend,season,cycle,irreg]=dhrfilt(log_ipi,P,TVP,VAR,12,filt);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grid on\n",
    "hold on\n",
    "plot([log_ipi,trend(:,1)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grid on\n",
    "hold on\n",
    "plot([season(:,1)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(irreg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## diferencia de la tendencia\n",
    "dtrend=diff(trend(:,1));\n",
    "grid on\n",
    "hold on\n",
    "plot(dtrend(:,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VAR2 =\n",
      "\n",
      " Columns 1 through 6:\n",
      "\n",
      "   5.1570e-04   3.0323e-07   1.7877e-06   1.2954e-06   1.8569e-06   4.1258e-06\n",
      "\n",
      " Columns 7 and 8:\n",
      "\n",
      "   3.1619e-06   9.1615e-07\n",
      "\n",
      "P2 =\n",
      "\n",
      "       Inf   12.0000    6.0000    4.0000    3.0000    2.4000    2.0000\n",
      "\n",
      "TVP2 =\n",
      "\n",
      "   1   1   1   1   1   1   1\n",
      "   1   0   0   0   0   0   0\n",
      "\n",
      "oar = 43\n",
      "NVR2 =\n",
      "\n",
      " Columns 1 through 6:\n",
      "\n",
      "   5.8800e-04   3.4665e-03   2.5120e-03   3.6006e-03   8.0003e-03   6.1312e-03\n",
      "\n",
      " Column 7:\n",
      "\n",
      "   1.7765e-03\n",
      "\n"
     ]
    }
   ],
   "source": [
    "## FIJANDO EL MODELO\n",
    "[VAR2,P2,TVP2,oar]=autodhr(log_ipi,12,[],[24:45],PaP,TVPaP,1)\n",
    "NVR2=VAR2(2:8)./VAR2(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "[trend2,season2,cycle2,irreg2]=dhrfilt(log_ipi,P2,TVP2,VAR2,12,filt);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grid on\n",
    "hold on\n",
    "plot([log_ipi,trend2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grid on\n",
    "hold on\n",
    "plot([trend(:,1),trend2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Tk36/P7V99jsPDg6eP38+HA739/cL/gGT89TjCQFrSSGLdCHE2RMiKzRl1+/3B4PB/v7+1tZWlmWdTicviaa2z27597//PfUNBU2d7vU+9wfACoq+OqjT6dwZKrPbp7bc9w9XIHsgdfmsXbk/0xxgchr7Lrs48+NQGSutcxuHX/KmkElpST6QLr+/Vh7BaqoZty04h7Hz5FMpO5NHkWBOUfKBNMfkxWasRNvUO5UdpFZz4acl7UD69urRzpNPde8FldK/NFWEAKNeaQcSbePGQLMVn7WbrcycMAlJOJAWmZGwtKGRdDHQSKkGkqXeLVdKJkm17D+DtvVlvEuVxaUaSLkgN06pRrmH2+xfTGY12izJQFpqzOX8poXUJaQovUBypVGc2jqmgjWrw5q6xAKpSBqZn2mYUg6osyIgsxqtlUwg5Z8rsVoaOb+hFuYzWEoagZSf1s7sNjMbsz6lj9iKH6xyd0kdnIpCHz9RgfykFEWUSLZBTEEDaTw4KiuK/hxwec8QQFRBp+zyCTqFERVozHxOwyq/ZWftGvbnt1PQQIJFNCZLyhVkKcFqu+GYtlnCgbTsgGgdH0lJNQx+oQ0SDqTVGHy1nGxLiAc22ibooga4z2QPFWFiqhmefv5x+epRlmlP6tS6ComkjZ9Iy/8ra/jsvkVYiqRWaVcguY2UovEk2+xNcgc0rCALK0hLuwKJdN3XweUjaIPoUgQpE6cK1kWKpAdvDSqCk5BqILk13Srzh9s7Tz6Z2InDtcnKUg0kWmLx3m2RUqkNfWUj58oMOFqidYG08+STMzsti/ew45UOK0zimdKB2ln2TRXGff2yBcrl99fLjvfH3+/NvEsJvvI7H2o4ms2WZCC1YeKleVYoQQp2QPm/nSyVLrMsbIfbJJKD1SQZSDApj7r7xiiTPePG4ZdLZVOy5hdJpX9EANVr3T2k2+Nf3Uaqy1JF0rdXj3bW8HEhk/eZSv/hlOW+U+XO1Q3fXj3Kp3bLfVya6qVXIZmvYzWTZ07zuq32XBezx27nyafJv93dpnS1rkKieiv0lXl5tPi/WuEG1Wy/ZqFdKiZfHzXncenqd4yCBBKVCtXp67bWYYWFkZBLLJDKmpfQE0VmvmVlBZuuSbdXVcApSiyQaDxplDQ9PkUIJAIpkkbzx7/31dZq5QZzcJMjkIhC38EkM2wt1N5AMnqqxmxpcmdHM/7kvQp37U/OhKTNv6/s4KalvYFEHLMzdautXpmMuo3DL5Nft+QZndpZYkcRKQWSboWlrDDn0/JpItcX9UopkEqnnI+g3GV1eaKMxy7zX3M35kwYC7Xyu5TxgYObkDYGUstHwdn/TmfVa02LvCcTyKgfUtHGQJrU2tFT7amcv9503WnUKh7hInVtD6QWqvJW3J2/K383886TT/f1nrXcLGzt0KQNHNxUJBNI6+uknKxVqnF5N+u2jk8MWe15ZxKVTCBRuupn7cwpNV7weKh9ppr5BFKWtalIqnFEOZVGU11DnHUWQF0EElWYXxtNxmSNkZnuuKTcRovWDsqa9hBIf4p2EVaj3kt96pmhIHR/jdTOCzw56X2E+fr45OM1mdOqUw8MRQsnoEppVEiV9VPjYVQjx8gVd/cr/DpplK51LLGbr3nDl0Z2O0tJI5Cq1OxMql5aRaeJHerV8m5HIN2tYSMvGi+t4F9WG15qlxd8Lb+F2dJAmn/U8/dLTn2WQVW7VrW1XgDN7iUbLHjfnTVuvq5hf87KLGq4258X5MSc+LjXTvS8ccYDwSUQSHXdin/6+cflq0cbh5+yiRBqcKlUrrwZv72qez+Wlx/3LFPYLeHPUtjVsZKpLm48adHCEWRLp+wWl8/q1r0XSTJfl6Kw9zCmptCbfVW29maSQJpndia9nWdJCznKy6osJIocmqeff1x+f13izsxR/BRqYW8jkP7H7EUV/+5uces47y+/v1YeUa7xo9MFk6+yXn6RXzQ/yNuWSdEDKUJtPpVJbTtFWqjKcXRYMYditfcGC1qt48o/tXId+5OKBBY1RLDsW4Ui5Oikivcnf2j/trLfByEt+DascQjlPcx0JlX7/ot6CaT/mn/qjAeMZqJgkiV2U5Ya/81Obk/9b6vWfIaesotWZ4xPlEU+xTL4tF4+ObCOKYI/y6NIBw7G1jofO/uxXvO7gkVeAJg/p1/O/oWnQlpOM94IPvUnfHv16Pbzj2jxX6+dJ58u0znQlpDEsfhFtODQ7fb4143DT5ftmJ6JWyGtu3+c/cTSBX9dzJu9i5sN1PwvKmXY2IC0Ziz1Uz2yZa+Up59/tOFwqJBWMedh/uB1xn2XwdPPPzYOv4xrgsmoXvbPCd4CC0roNRMbh18u694HlrLyuK3xd7KDVkhJdGrz7xLFuY20bPGXV0srPO2hPGohB/1BU13Bt4lh3wq93LhUauQa8aAVUvw0SvGNZ/P7jj+XqP7nZlJ+ri9+b6l5HVNat5FYXI1HtqzLpKmnZdAKqWKrDVWat/pl8rGJlsxZQ1ke7EZWTqM40y3rJpAKmeqyI880LngxzL45aZHFDgVnIQhlsvtbcFDiuD9o6gLUYndqdSAVHHc8+M+bMa55sBBs3mQdC0r00FefBJffX+/c9eFqTGl1IJWiDfNa9/2N+W3VFLukBbXh4LZTlfPtk/MH4ydnlUd3CrqooUrFa+fIT8uOVyisvHt5nXf5v8PhZq89zY3/cFjZ+KqRQItoe4VU1lkyfra0qQPqqcWm+f9OfY9p8UUk90kfc+rjZo9IiiuxiZox//+gtgdSViyTpm7/7jz5FPCzKkq8KvIc0g0VVPspQQUE9goEUmkmF0w3tU5qoXKPpiKyqRzZUgiktZBJzBGhbl7K7PncgOH/Wi/SdbRPcqfNCgRSUZHPko3DL5W9B9oI8UGaKI7Il22bCaRyzPY14/FXA079BvwJRah3s/9thAaUR2ulfVZm2XcJ7hv2Rl4OTsUaUB41/lXT1E6F1GTm6wpqeWk4q2FrLNdR+651DNr4E1IgrVd+xjf+NGq8gj3XbGA7JWCWQGqsdc8Wjl+CQss1tT5e3LgFTNEXJJDWrhlF0uT+51GUf4Jf0n9UA6yp/R1ZaiGQWMV4RDz5EUpUr7LbhE1V4m2kasqjZo8VBFIVqi+Svr16NPm6+7VqSRpZ/N0wze7ZEyWQGmtNOdG2eki3BZURSBWpcny9pvJI1wwRNPhKrCeQer3ey5cv9/b2RqNRLTtQiwU/DjyyfCFD3XtRG7N2jVTKYbW+rhQ1BNJgMLi6ujo7O9vf3z85Oal+B+rV1KEN92nbJGfbOL4lqiGQvn792ul0sizrdDqDwaD6HahRBUVSPl/nClkTRRKzqi+PmjprV8+U3fb2dv7F1dVVLTsAi1vTxd/UPiVFxhlB1BNI19fX+Rebm5t3fsPGhAr3qwpOfQgi6TFBwJ0v3m/XEEiPHz++uLjIsmw0GuVzd7NuJ1S7d2lzZ7UCLRlSLNjfuYNS47PJ0Vq+eL9dQyB1u93hcNjr9Y6Ojt68eVP9DtRu58mn9fVoOghYQUvGGcHVM2XX7/efPXv24cOHn3/+uZYdaCTlUdtU+T4OqEBtD8Z2Op2tra26fnvtDMfSMjV/tfjhU7A2mzFBubypoQbzZ+ej3aiEllhtmGjAUSKBVJs7z/58QL1CJpmvq5gaF0onkOqkU4N6rTwZm5mvWwOBVLPJC2Dl+w3j8sgdi/WZrVyNJ6BcAql+s/1awEfeWIHxASxFINXjzomCguUR1au9SBJ4pVvwmLru1kEgRZE/LTu+EhRJAd15UGrPpBo1owR0rcUhkAJ5+vnHsr2bYVpYDeisW9tTP3gZuu7WRCCFMNl5jS+GB7sDV0UQKxdJre3xm6EBY45oBFJEeQeX31XaOPyiz4qv+ok7a45LtNQSSgPB9RFItRlfA3eOs8bTd5ffX89eLXlcTV0VxmsVmFPTlLKCnzjuzCRptFY/1b0DrZb3bnN6rvzU//bq0WWWfXs1vZ1o/tuFqV1Sc+fFOJtJLr21Ekg1W2QcPb4GjLvje/r5x8bhl8vvr7NMz5WY+zKprv1pIVN2UL42rAU3PKJ0Aqkh9A6VefBl7fmBaEMmNY91j/USSClxtaRFJjWYIeA6CCRYI5kEixNIiVEkRXDfUbhvBX+6mdTC862Ff3IcAqkJzB7UZcGeK+lMgsoIJFhFvePo2h/PNAZiHQRS8nQNdbk9/nUylh58xlmRlAqzdnURSOlZvBME1sF1tybe1ACFjMcHD/ZQeZHkyX+4jwoJisrn7lb+t2aHApo6Lo5RNQRSksYfS2HeoLVqPPptO/Hyv3dynrze/WkwgQTVSXFpQ5truMk/fHIU2Ko8rpJ7SAlzVcD65NfXZDnoils3FVKqXBuJSrFImtS2+bpW/bG1E0jAA9o8a0eVBBIAIQgkSEyNDzO1bb6OigkkqFqKt5HM2lEBq+yAhaiNWDcVEgAhCCSoQYqzdrBuAgmAEAQSACEIJABCEEhQMyuqISeQoB6rrWvwEX80mEACIASBBEAIAgmAEAQSACEIJKjNyu9r8NZtGkkgARCCQAIgBIEEQAgCCZLhqViaTSBBnXwOBYwJJABCEEgAhCCQAAhBIAEQgkCCmj39/OPy+2sfiQQCCYAQBBKkwUNINJ5AAiAEgQRACAIJ6peva6h7L6BmAgmAEAQSACEIJABCEEiQAGu+aQOBBCHsPPnkcyhoOYEEQAgCCYAQBBIkZuPwy+3xr3XvBZRPIEEU932cuRUNtIRAAiAEgQRACAIJQrg9/nXj8Mt9s3bQBgIJQnMDifYQSACEIJAgFrN2tJZAgojyTDJfR6v8VPcOANPyEJJGtI0KCYKSRrSNQAIgBIEEQAgCCYAQBBIAIQgkAEIQSACEIJAACEEgARCCQAIgBIEEUeQfiVT3XkBtBBKkZOPwy+3xr3XvBaxFoZer9nq933//fXNz8/3799vb23O2T23Z29vLv3N3d/ft27dF9gGAZli9QhoMBldXV2dnZ/v7+ycnJ3O2T225vr7Osqzf7/f7fWkEQG71QPr69Wun08myrNPpDAaDOduntgyHw+3t7V6vd3p6WnT3AWiKQveQxtN0V1dX87dPbhmNRjc3N8+ePfvjjz+Ojo7u/MkbE4rsIQDVKN5vL30P6fT09Pz8fHd3N8uyfPIty7LNzc3J75ndPrml2+12u90syzqdzi+//PL+/fvZ33J7e7vsjgFQo8l+e2dnZ4WfsHSF1O1283s/jx8/vri4yLJsNBrlM3K52e1TWz5+/JhP5V1fX08lGQCttfoqu263u7e31+v1hsPh4eFhlmWDweDk5KTf709tn/3Og4OD58+fD4fD/f39sv4SAJK2UXBybDAY7O7ubm1tPbh9ast9/zDLsp2dncvLyyJ7BYl68DEjzyGRhNW68ULPIWVZNjlZN3/71Jb7/iEA7eRNDQCEIJAACEEgARCCQAIgBIEEgfgECtpMIAEQgkACIASBBEAIAgmAEAQSJMN7g2g2gQRACAIJgBAEEgAhCCQAQhBIAIQgkAAIQSABEIJAgli8X5XWEkgAhCCQAAhBIAEQgkACIASBBEAIAgmAEAQSACEIJEiDD0Oi8QQSACEIJAjHyxpoJ4EEQAgCCYAQBBIAIQgkAEIQSACEIJAACEEgQURWftNCAgmAEAQSACEIJEiAF9nRBgIJgBAEEgAhCCQIykI72kYgARCCQAIgBIEEQAgCCYAQfqp7B4B7jdc1eAiJNlAhARCCCglCUxvRHiokAEIQSACEIJAACEEgARCCQAIgBIEEQAgCCYAQBBIAIQgkAEIQSACEIJAACEEgARCCQAIgBIEEQAgCCYAQBBIAIQgkAEIQSACEIJAACEEgARCCQAIgBIEEQAgCCYAQBBIAIQgkAEIQSACEIJAACEEgARCCQAIgBIEEQAgCCYAQBBIAIQgkAEIQSACEIJAACEEgARCCQAIgBIEEQAgCCYAQBBIAIQgkso2Njbp3oV00ePW0eRJKDqRer/fy5cu9vb3RaDR/+/n5ea/XK/e3A5CuMgNpMBhcXV2dnZ3t7++fnJzM2X5wcPDu3bsSfzUAqSszkL5+/drpdLIs63Q6g8FgzvYPHz789ttvJf5qAFL3U7k/bnt7O//i6upqke332dnZKXfHmOPp06cavEoavHraPAlFA+n09PT8/Hx3d/ft27dZll1fX+fbNzc3J7/tvu13ury8LLhXACSn6JRdt9vt9/t5Gj1+/Pji4iLLstFolM/R5e7bDgBjG7e3tyX+uL29vd3d3eFweHh4eHNzc3Jy0u/3p7b//PPPWZblS+zyJAOAkgMpy7LBYLC7u7u1tbXgdgDI1hFIALACb2oAIIRwgXTfux4oy9Q7MqYaXPuX7ujo6OXLly9fvswfwpttYW1eouvr64ODg7w987VUmZN8/a6vr//2t7+N/3flBo8VSPe964GyTL0jY6rBtX/pTk9PNzc3z87O/vGPfxwdHc22sDYv1z//+c+//OUvZ2dn3W7348ePmZO8EsfHx+OvizR4rEC6710PlGXqHRlTDa79S7e9vf33v/99/L+zLazNy/X8+fP9/f386/ypRyf5up2fn29ubo7fflCkwWMFUrb8Ox0oaKrBtX+5Op3O9vb2aDQ6ODjIO8rZFtbmJdre3t7a2ur1esfHxy9evBhvzL9wkpduNBr961//mnqAZ+UGDxdIS73TgeKmGlz7l67X6x0dHR0eHna73eyuFtbmpXv79u3Z2dnR0VH+v07y9Tk+Pt7c3Oz1eqPRaHxzeuUGjxVI3ulQsakG1/6lOz09vbm56ff7+fPgsy2szct1dHR0fn6ef31zc5M5ydfszZs3L168ePbs2dbW1rNnz7JiDR7uOaTZdzpQrql3ZEw1uPYv19HR0XA4HA8M+/3+bAtr8xJdXFy8e/fur3/963A4fPHiRV6VOskrsLe3l7+XJyvQ4OECKfNOh8pNNbj2X7fZFtbmJbq+vh4Oh/NbWIOv22oNHjGQAGihWPeQAGgtgQRACAIJgBAEEgAh/D/eIO7WiftskAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## diferencia de la tendencia\n",
    "dtrend2=diff(trend2);\n",
    "plot([dtrend(:,1),dtrend2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VAR3 =\r\n",
      "\r\n",
      " Columns 1 through 6:\r\n",
      "\r\n",
      "   4.1137e-04   1.0402e-07   1.6950e-07   2.1662e-06   3.3848e-06   6.5170e-06\r\n",
      "\r\n",
      " Columns 7 and 8:\r\n",
      "\r\n",
      "   1.4527e-05   3.1710e-06\r\n",
      "\r\n",
      "P3 =\r\n",
      "\r\n",
      "       Inf   12.0000    6.0000    4.0000    3.0000    2.4000    2.0000\r\n",
      "\r\n",
      "TVP3 =\r\n",
      "\r\n",
      "   1   1   1   1   1   1   1\r\n",
      "   1   0   0   0   0   0   0\r\n",
      "\r\n",
      "oar3 = 34\r\n"
     ]
    }
   ],
   "source": [
    "## FORZANDO EL MODELO CON LOS PARAMETROS DE DECISION\n",
    "[VAR3,P3,TVP3,oar3]=autodhr(log_ipi,12,[.1,.45,36,500,2],[],PaP,TVPaP)\n",
    "#NVR3=VAR3(2:8)./VAR3(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VAR4 =\r\n",
      "\r\n",
      " Columns 1 through 6:\r\n",
      "\r\n",
      "   5.1285e-04   3.4577e-07   8.5823e-07   3.6727e-08   2.9791e-06   4.9786e-06\r\n",
      "\r\n",
      " Columns 7 and 8:\r\n",
      "\r\n",
      "   5.2153e-06   1.4846e-06\r\n",
      "\r\n",
      "P4 =\r\n",
      "\r\n",
      "       Inf   12.0000    6.0000    4.0000    3.0000    2.4000    2.0000\r\n",
      "\r\n",
      "TVP4 =\r\n",
      "\r\n",
      "   1.0000   1.0000   1.0000   1.0000   1.0000   1.0000   1.0000\r\n",
      "   1.0000        0   0.8090        0        0        0        0\r\n",
      "\r\n",
      "oar4 = 35\r\n"
     ]
    }
   ],
   "source": [
    "## CON INFORMACION MINIMA\n",
    "[VAR4,P4,TVP4,oar4]=autodhr(log_ipi,12)\n",
    "#NVR4=VAR4(2:8)./VAR4(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "[trend4,season4,cycle4,irreg4]=dhrfilt(log_ipi,P4,TVP4,VAR4,12,filt);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## diferencia de la tendencia\n",
    "dtrend4=diff(trend4);\n",
    "plot([dtrend,dtrend2,dtrend4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "load data/vabindus.txt\n",
    "log_vabindus=log(vabindus);\n",
    "plot(log_vabindus)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "[logipi_trim] = acumula(log_ipi,3,0); %trimestralizacion del IPI\n",
    "plot(logipi_trim)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VAR5 =\r\n",
      "\r\n",
      "   9.5970e-05   4.6138e-06   3.7948e-06   3.1461e-06\r\n",
      "\r\n",
      "P5 =\r\n",
      "\r\n",
      "   Inf     4     2\r\n",
      "\r\n",
      "TVP5 =\r\n",
      "\r\n",
      "   1   1   1\r\n",
      "   1   0   0\r\n",
      "\r\n",
      "oar5 = 24\r\n"
     ]
    }
   ],
   "source": [
    "## fijando el modelo\n",
    "[VAR5,P5,TVP5,oar5]=autodhr(logipi_trim,4,[],[],[],[1 1;1 0],1)\n",
    "[trend5,season5,cycle5,irreg5]=dhrfilt(logipi_trim,P5,TVP5,VAR5,4,filt);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## diferencia de la tendencia\n",
    "dtrend5=diff(trend5);\n",
    "plot(dtrend5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## filtando log(VABINDUS) con el modelo de temdemcia del log(IPI) \n",
    "[trend6,season6,cycle6,irreg6]=dhrfilt(log_vabindus,[Inf],[1;1],VAR5(1:2),4,filt,1);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## diferencia de la tendencia\n",
    "dtrend6=diff(trend6);\n",
    "plot([dtrend5(21:118) dtrend6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot([irreg5(21:119), irreg6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VAR7 =\r\n",
      "\r\n",
      "   1.2193e-04   1.4162e-05   5.6987e-06   2.7896e-06\r\n",
      "\r\n",
      "P7 =\r\n",
      "\r\n",
      "   Inf     4     2\r\n",
      "\r\n",
      "TVP7 =\r\n",
      "\r\n",
      "   1.0000   1.0000   1.0000\r\n",
      "   0.8936        0        0\r\n",
      "\r\n",
      "oar7 = 25\r\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "[VAR7,P7,TVP7,oar7]=autodhr(logipi_trim,4,[],25)\n",
    "[trend7,season7,cycle7,irreg7]=dhrfilt(logipi_trim,P7,TVP7,VAR7,4,filt,1);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dtrend7=diff(trend7);\n",
    "plot([dtrend5,dtrend7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "error: horizontal dimensions mismatch (1x98 vs 98x3)\r\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "[trend8,season8,cycle8,irreg8]=dhrfilt(log_vabindus,P7(1),TVP7(:,1),VAR7(1:2),4,filt,1);\n",
    "dtrend8=diff(trend8);\n",
    "plot([dtrend7(21:118) dtrend8])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4jg7dFGoyNgRSFLiqAbN4iLgJBBIAQAQCCQAgAoEEABCBQAIAiEAgAQBEIJAA89ivDFRAIAEARCCQAAAiEEgA/vP19Q+ui8Azp/EikAD8PxIyCXEikAAAIhBIMIzxNYBqCCQoxTblBlClMeAsm0UgwSSb0yM6ArPYSgDnCCQAgAgEUvgY+QLwAoFkXqmlJNadqqHegPCICyRuEgJuPfv47e7v312XAjESF0gAgDgRSIYxvcMK0/36qMOoEEgAABEIJACACAQSgB1YKIN9BBJgEq/yAyojkGDM19c/PPv4zXUpXPJ9tzRnEG4RSCbxTgSl1LOP35gl+I5HkeAEgeQSy/QAagqpGyGQYFhIl0cp0f7hgCkEEqJAWgDyEUjwFc/wA1owFwKBFAvuUQMQjkAyRuYWO5mlglLq4PxLMANbwAgCCSbJ7GFllkq4o6cf2L4PywikiNAvA0aw8NAQAikKFoa6POQPoCYCCf5hfGocVQoJCCQAgAgEkhkMMKHxKj+gMgIJAPwWzEPiBJJ5wTQOALCJQIJhLF0GQ8jyIyO8eBBIQIPoTIHiCCQASvEkGQQgkAyos8XO+Qia/YEAhCCQDOBF2ht4DRri4XxMGRICKXwWlmJY7QFQH4EUMpbjAHiEQAIA74WxclgrkJIk6fV6g8Egy7L847PZLEmSOr8L2BbGRSgTdQv7qgdSmqaLxWI6nQ6Hw/F4nHP87Ozs7du3Bgq7Rc4Fwz18BEnIs7GIRPVAurm56Xa7Sqlut5umac7xq6urN2/e1C4qACBktZbsOp2O/mKxWBQ5jrBFvofi7u/fi281jLyuzGIOF4xagbRcLvUXrVaryPF9DtbUKY9f6JIAhKR+T149kA4PD29vb5VSWZbpNbr84zke1lQuD/I9+/gtjAd45Qe5tPsuB+df5NxtRcDq9+TVA6nf78/n8yRJRqPR6elpmqaDwWD7eOWfDwCIypM63zyZTNI0HQ6H7XZbKbWaD20cV0pdXFzULKhwelDM2wrE0puYhU+tUBlXnwqikdd9MLbb7a5Sp8jxIngAwi/bfYHXlwTko38IVa0ZEpRSX1//cPT0g9h7X4wcEQxyKHgEEhA7vc7z9bXrcuTaWIzyfW0KOxFIAKQjeyLBy1WB8D16X9bfpV1/S25EYDNFAskA3SCkPX0CAH7xPpC4z7lP2aGT2c2NfGgskIOOayfvAwkQjscYgII8DqTAFk8BFEfM7+R7tXgcSACAkBBIQBR8HzsjBgSSSWy0s49+FpZxs6A5BFLILDyiIf8pEDvdB6EI1EcgAebJmSsznBeLQcw2AglAHjnhuuHh8oX8Cbp9Xi9iE0gwY2Mk3tConPE+EDACCbDNVax6PXZGDAgkw8SubwBlOQkwJsExI5AAICj+ToUJpEaYahCetirAMrcrE/4GgDQEEgBABAIJgMeYmoSEQHKMHRBhuPv79woPxAhZ6qlWeEgmpGmVRSC5wVYiOOFpPxWbOufI6zEugRQs58NePjQWQCkEEhA1IROmCmMXf98b1PQCia5MH2fDBBIQL1EdFvNpEEguNXcF7uxoWEPDysH5Fz1O9/1epo/zAOxDILm374oyfpn53vXAFCdRxGDIGn9fYEYg1fL19Q9HTz+4LgUkWu8Udo45vr7+oeleY+e9igBmRSjIu+mj94EksMb9HZ54qmAbENhUYsN10TR/N3po3gdSZfRN9eW3fobhQEFEtRZvIHmBQT1Qk/wrSA/szGaSp+s0BBK8westVizcf7KvuT5UcibtW2YwVeY6g1r79UYgOebpQMaJu79/d12ESDXdSn2/81HNw+WLOP/wHJEGkuQRk4+szV2CCW96IoM8Xdnet0fX1NXk42A30kAqy7vz6vxFdg3R15h3p2NdnAuPxgPY90TfLr+P+WEcgQSlfEjc1XDy2cdvXLpAcR7dRvI7kCLvlWL+88kkbKBJBEBoIIlaFM5v5REuvwDVkBmW1alwJ2vLQgPpUQEsxPu+CI4wxNAORQ1wc3gd2EZK7msgAQjPs4/f2NxfWQBjC3GB5O8AwTIjFaUnms3VuZwPvBBSDM2jjsOXuQXy+XIexQVScaK6GNhXdn0jsAbj9fIOsJPHgVTZ6sNgvBgyoD5XMxIyowjJ80X7XYTxRcuajbBgP2nqJMYYSBawFC4QJ8UVh5FTc/fT3d+/bzyIHcB2KsmeuC4AQvZw+eLra9eFWHP09MOd4PF4ZXoMu9FRBtx12kw4/Yv+yyQTH8gZ6otU6vN7hmRhSUTyegIqiGEZLfg/sILKS/T6u/T7QbyeZDd9k8LIDxcXSDL7C5mlkrOHLUejhXz0vDifJWyX0PjoeOffKLZhPHrKhLfqnOKZKrbwGmiUuECKgfNesiz5uz9Kjf6MDy/2vbYZ8fB35rSTqz6KQJJO7G5AFjMRp+0BTeTXgsE/n0BC42QueFrTxIRsdf17N9tuiOVx2/o5Ldsdyxxf1mSqHRJI7hm/UxreCpL+iyT3vI+WTeZMN/KhfR2rj+ZaVaDbez85p3IVn9Uaoc2mG10gCRlR0hFEZd8kqeZY5Ojph9W3ywy8R9m/EIpnRpGBnfHCC+mgXAkhkPZdivktr0i7rHm1eNRBNLeqps9Ocz/fr/VAC5NX4118zaiT81mxxjPb+ZgyvPTyNZBq7p31qAvbyeai3KPXcHhXBbbZDP6mf1epH97o1NPTeW1zfA2kgnwPHsu4PJqzWp0zFd754wCvH+GER8zOgAMPJGxweN/Vr7U1BMmXd/b4NZ4wuEYSYyCZivRG181YBzOF/SPScENROIedT+CBFPNLOAoq0l/f/f17naU8VgK1o6cfTI1gGK/YQSVbFmwgMS4WqKEBbIUfG+RQOobgD+C6drJsaOdTkeqTGEgGO4uHyxcbkyRrrcGvVeBIBN9l+3KPxI6d80iPGkATRRV+CUgMpFJKpVepMyF8LKavtH1/PksNkKDyRRTkFLY5rjor47/X+0AqhfEjArOv47b5sdOVWS6A8783SGZvZ0YRSIy26jCy8Ch8oSBIwpu98Pawvoc22tZrv/2EH0j7GpO+x+N1O4v2Otlm9o6d5H4csMnyteBlIFV4AEiPFgN7B7Y1UW3QII2EED7DQxO8DCQnDF4e9V/El5Os5G7kvNiatf6e8uLybwIVLyRP5uZY3RPStW35L4ookPy9nxnG0lzl135zL7ogKioHlWP8UaQmqjSiQIJBli/vgjt5AojtRwXQsfKaCb/kJJnxU2kjkJIk6fV6g8EgyzILv25bhRmG/cs+hs40DMbPFKd+nwBWwFBK44GUpulisZhOp8PhcDweN/3rtJ1XuORxWVS7BmziyTOHApjMWSanj9o4dxsjg43Pbjeo8UC6ubnpdrtKqW63m6Zp079OoxuyRs4lVFa10TezmZqcN5hqd2TDuI9rxGqzQxM/3MaSXafT0V8sFouC3/LojEFIJyikGHbUvyC5qpuwkazrlSx8ycvadlA5c7UmNsHa+et0n9z077IRSMvlUn/RarV2/gcHaxoqQ83kcNWNSu5NpJG/7Gnns2Ilq1DyVabKCZV9gh9v6YlRzt9YvydvPJAODw9vb2+VUlmW6bW7bQ9rmi5PBWYbmZGfZr8/kt/dG9F0rycnSJz375LTxXnlKMFX3Cp3t4cX9XvyxgOp3+/P5/MkSUaj0enpadO/Lof9vsDOxwMKX5bZsP2BIALZrFJT/Y6FPtSvluYLm/Oqgmfw0bbUXJltLNlNJpPnz59fXV2dnJxY+HVmOVwesXDxr+/+sNbdyJklGMGrMQqycymtmrHYhU2ZpdKKV1pDf4WlB2O73W673S77XTtDePv6D+A1qfsYDwk5F0OQ5ytyDZ1TJzMzsXlWn6n5TRP1w5sa8gTcKAsiNjwVebtdt3MBqvKmfyq2UQTSDo0uxzf6ZlWPBL8lyaEmOs2C5yvycxpAXLnd0EEg7cVoqGlkkgXB7ERwvu2tYG8gf8+OZFEHktiNlZXJfOdpYMjR5uxrUZVbtYQN3KIIH6AEGEhGOos4u9ptzl/CVKpDiXZw2tyrXPwS4VihQuJKHogHGEhNcNjQ5Yxowuvut18ZSbeOGOy7lp0PQAMMJOd1asTGXxHY0M9OyhIwkaMB5JAz0l0nN5CszStD6uiDxPLpCj2sBTUr2aO2qjNp/X+uS6SeuC6AT/T5041Vb7928uq9mi3+6OmHu0qX3MPli6+v6/xmSBFDsAlcKXHYaeyzUUUH51/cFk/uDMktt8Mc4ZO2GLozlBXDRDbsP1DCGfQskHzvCnMea83ZMiBztTdsIdV5SH9LwHbmgfCxqXGeBZJfrA036HE05+M7CyQMY1fEtrpgXmgSGwLJHt+ndxuM9IyB7R4Uq4khS/4PlN/aGcYJRCA1K7Bnd+T/OY+WsIkIlDNlsUPvyNJP4wpvD64YaWOSn2BtSCCBZPDMNTTZLzVg3LdBiIWI5sgf0ddUPzx07q6iyFC5zHv28dvR0w8xjBIE7iSsKZBAWolt/afOeN9tvHk9uI52pfHo6YdqPaCoW18QK7RAkmk1+q58WUY4eYdxXg8CYJDYEZVPgeTvoorYN3AzaC3VRzPMRxEMHyvzKZCKCG9RtTh/AxvWMElSufMDfRFZHnmIna/YJzqQ1ndM2extzbZFQgLBY+64jYypQHQgWcDkWrI6oxCPdiRa3kwvfI9cTcw2qhEypPAjkFiMUkrp7rXRRkM8wybCAxv8CKSoyBnab5fk4fKFPiJkPLWTqdsk3G6pwOuMaXTgy6i6CA8CqfiJbPRKkHClCQkqsyRUbOXOQs7oAQiAB4HEsEJzMiPZ+UtNnZEiUxDJUzH4zvIk2GxjDnIw5EEgBaPRvpXYDh5rPo0yXr0Spv7ekR5I202EITMadXD+pWA/Yj8hnDd+OllRwusJpQeSHatr7NFZMDe6zfK3PsPrC2LG7FMIAqm6ULukmIfAxacgQa7goyFFAi/U/qQUAkmQmtMFT4d4PPzkO+cLiQhGOIGk+7X6nbLzSyvnT3BetiCtKpyONRilziPrdXKEE0iwxnjHbfDdOdXuupftj2LuwjZqmAnuTuurHXVai53XSskZihFIUljevyTtFojZ3Q0VXtcm55qEZc2NLSRvSpRZtieuCwBsWiXTs4/flLxrJubpkRdKDSyEnEoGQxqBBPf0YO3h30mS/T5i3/RIz9uE9FkeodJWGvqENr3C8WD857pGIFlScEUo8ss48j8fiBz3kFBOeGsLpe4eMfZX5W8/cH8OBQUVSNZ6Cmk7AgCYQnw6JDqQ7OwDiXDfas3kDulyLdX7NHQ/IKT6xLr6I9fY2oboQIoTAzRfyNw4C1FoJKUQSP95tN1E1bZiWJYse/co+AqpIJ4rAhYQSP9paEEGlUmbLIoqjFtRDc4qoz8pi0BCmOqEmcDe9vtzJz4koheFtIA0qoBAQnR03rBeFzOBYw5XRK1DEEg2NHrKzV5aEe45lMDOOzQB4QgkRIqHYeGpgBskgdQssSsD0ho0FeUdsadMGiqqOAKpNHqoAPj4QmggeATSdwxhAMAtAgl7ydl7A8nMfrgiNjS34UXgWiKBFB2BrRD+YtRSkKmttgHvaFB8HhJQh53u+HsfJG8YQRrBLGZIQRH1jJsrTAERqrCnR4pAsoOQAHaKZPRAD1AQgfQdb1YFIFlD0yNRYUkgKVX+QROiy4IYBs4A1rGpARJxM8xf319M/u8//TqVfpU2PMyQyolkyduJVd3SKWyjTiIX/HYGzbNA4rIMHqcYiJZngeQjH7tXVx//83D5Qkh1yZkKRzI0Dl7Nht1QGxByua1IDyQ5/QIAoFHSAwkAIhfPFJlA+q7UKec+BwAY50EgsWoH+IVrFtV4EEgAgBgQSMDjWKQFLCCQAECuqNY//QikqE6Jc06eQILXn7vqdeEhhx+BFA+WhrAuqqdinTd+5wUAgQQgRqy7CFQrkJIk6fV6g8Egy7L847PZLEmSOr+L1oPgsfCFyFUPpDRNF4vFdDodDofj8Tjn+NnZ2du3bw0UFgAQruqBdHNz0+12lVLdbjdN05zjV1dXb968qV1UmMRyOQBpai3ZdTod/cVisShyfJ+DNXXK47vKCWF8PfPo6Qev48rrwgOeqt+Tlw6k6+vrwWCgbwgtl0t9sNVqrf83+47v87Am7z+jl0HouI0EfxXsyXOUDqR+vz+ZTC4uLg4PD29vb5VSWZbpNTpt3/FgkIteCOk0sb6KSFRfsuv3+/P5PEmS0Wh0enqapulgMNg+bqykSqmwehkI53xjZ1QPIQFKqSd1vnkymaRpOhwO2+22Umo1H9o4rpS6uLioWVAgEnrVLowoYm7XkFArtu6Dsd1ud5U6RY5DviAbOuwIJkrhBG9qAIBg5xx+IZAAACIQSIA4bP5GnAikKpjaA4BxBBIA85xvmoePCCRAomcfv0WyXY3owgqBBMAA7nuhPgIJcI9ZAqAIJGnqbJfgQQoAXiOQAAAiEEjAI5h6Bk/4KY5nRZdAAgCIQCBhB8mjRQChIpAA0YSvJgEGEUjAXvGs3QMSEEgAIsWAQxoCCQAgAoEEABCBQALQFLZjoBQCCQAgAoEEwJhIPjIDDSGQYsRCCrDCk15yEEgAzNiYHtHLGxTJDnUCKRBc/AB8RyABAEQgkAAAIhBIAAARCCQAgAgEEgBABAIJACACgQTIxTObiAqBBOQhDwBrCKRw0HU2hIoNG+dXDgIJACACgRQpRoWA8upCiOF1dgQSAEAEAgkAIAKBBMCxGBajUASBBAAQgUACAIhAIAEARCCQAAAiEEgAABEIJACACAQSAEAEAgkAIAKBBAB+CP4JYgIJACACgQQIxcfFIjYEEgD4JOCRCoEEABCBQAIAiEAgAQBEIJAAACIQSIAIwT9i8qhQb9SjOAIJACACgQRIwSQJkSOQAAAiEEiAIEySkC/sO20EEgBABAIJACACgQTIwqodokUgAQBEIJAAcZgkIU4EEgD3wt48hoKeuC4AgB3ooBEhZkgAABEIJADwScCzZwLJJwcHB66L4A3qqiAqqjjqqmm1AilJkl6vNxgMsizLOT4ajXq9Xq/XS9O0VmEBAOGqvqkhTdPFYjGdTtM0HY/H796923n85OSk1WpNp9Plctnr9T5//myo5ACAoFSfId3c3HS7XaVUt9tdn/psHO90Or/99lv9ggIAwlZr23en09FfLBaLfcd1OGVZNhqNhsPhzp9zdHRUpxjxePbsGXVVEHVVEBVVHHXVtNKBdH19PZvNjo+PlVLL5VIfbLVa6//NxvEkSebz+fn5+cnJyfYPvLu7K1sGAEB4Si/Z9fv9yWRycXFxeHh4e3urlMqyTE+DtI3j19fX9/f3k8lkZxoBAKAdPDw8VP7mwWBwfHysZz/39/fj8XgymWwcv76+ns/nqymU/g8AANhQK5CUUmmaHh8ft9vtgscBANipbiABAGAEb2oAAIjgOJD2vesBKxvvuaDG8i2Xy19++UV/TV3luL6+1u1Kb0GirvZZ1YyuKEVd7TKbzZIkWf1zo4qK15jLQFq902E4HI7HY4clEev6+lq/5+KPP/4YjUbU2KMuLy/1F9RVjtvb29lsNp1Or66uZrMZdbXPbDZTSumaef/+vaJd7XJ2dvb27dvVPzeqqFSNuQykfe96wMrGey6osXyz2azVaunnsqmrHLPZ7NWrV2maLpfLi4sL6mqfdrutn/rPskxvFaautl1dXb1582b1z40qKlVjjj+gb9+7HqBtvOfin3/+ocb2ybLs06dPV1dXg8FAH6GucozH45cvXy4Wix9//FFRV3scHx9nWabXmlav66SuHrVRRcVrzHEg7XvXA1bW33ORJAk1ts/l5WWr1UqSJMsyvZxNXeUYDof9fl8p9dNPP71584a62mk8Hvf7/X6/v1wuf/3117/++kvRrgrYqKLiNeZyyW7fux6wsvGeC2osx+np6atXr54/f95ut58/f05d5Tg8PPznn3+UUsvlstVqUVc5dB/abrf1F9TVozaqqFSNOX4Oaf2dDrxbaNtoNNp4zwU19qjBYLD9xhDqat1yuTw7O9OV8+rVq36/T13tpNfrXr58uaooRbvaRa9JXFxc6H9uVFHxGnP/YCzvdCiLGiuOusqhPx1mtb5PXe2zUVGKuipgo4oK1pj7QAIAQDl/MBYAAI1AAgCIQCABAEQgkAAAIvwP16VXkZXDwLsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot([irreg7(21:119), irreg8])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Octave",
   "language": "octave",
   "name": "octave"
  },
  "language_info": {
   "file_extension": ".m",
   "help_links": [
    {
     "text": "GNU Octave",
     "url": "https://www.gnu.org/software/octave/support.html"
    },
    {
     "text": "Octave Kernel",
     "url": "https://github.com/Calysto/octave_kernel"
    },
    {
     "text": "MetaKernel Magics",
     "url": "https://metakernel.readthedocs.io/en/latest/source/README.html"
    }
   ],
   "mimetype": "text/x-octave",
   "name": "octave",
   "version": "6.2.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}