Created
March 29, 2018 21:29
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 14, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"%matplotlib inline" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 15, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"import pandas as pd\n", | |
"import numpy as np" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 31, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"N = 1000\n", | |
"\n", | |
"d = np.array([0] * int(N/2) + [1] * int(N/2))\n", | |
"t = np.array(range(N))\n", | |
"y0 = np.sin(t/25) + np.random.normal(0, 0.1, size=N)\n", | |
"y1 = y0 + 5.\n", | |
"y = d*y1 + (1-d)*y0\n", | |
"X = pd.DataFrame({'D':d, 't': t, 'Y': y, 'Y0': y0, 'Y1': y1})" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 34, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"<matplotlib.axes._subplots.AxesSubplot at 0x7f67a27b65f8>" | |
] | |
}, | |
"execution_count": 34, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"X.plot(x='t', y='Y')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 36, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stderr", | |
"output_type": "stream", | |
"text": [ | |
"/home/akelleh/.virtualenvs/data/lib/python3.5/site-packages/pandas/plotting/_core.py:1716: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access\n", | |
" series.name = label\n" | |
] | |
}, | |
{ | |
"data": { | |
"text/plain": [ | |
"<matplotlib.axes._subplots.AxesSubplot at 0x7f67a273add8>" | |
] | |
}, | |
"execution_count": 36, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"X.plot(x='t', y=['Y0', 'Y'])" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 49, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stderr", | |
"output_type": "stream", | |
"text": [ | |
"/home/akelleh/.virtualenvs/data/lib/python3.5/site-packages/statsmodels/tsa/kalmanf/kalmanfilter.py:646: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n", | |
" if issubdtype(paramsdtype, float):\n", | |
"/home/akelleh/.virtualenvs/data/lib/python3.5/site-packages/statsmodels/tsa/kalmanf/kalmanfilter.py:650: FutureWarning: Conversion of the second argument of issubdtype from `complex` to `np.complexfloating` is deprecated. In future, it will be treated as `np.complex128 == np.dtype(complex).type`.\n", | |
" elif issubdtype(paramsdtype, complex):\n", | |
"/home/akelleh/.virtualenvs/data/lib/python3.5/site-packages/statsmodels/base/model.py:473: HessianInversionWarning: Inverting hessian failed, no bse or cov_params available\n", | |
" 'available', HessianInversionWarning)\n", | |
"/home/akelleh/.virtualenvs/data/lib/python3.5/site-packages/statsmodels/base/model.py:496: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n", | |
" \"Check mle_retvals\", ConvergenceWarning)\n" | |
] | |
} | |
], | |
"source": [ | |
"from statsmodels.tsa.arima_model import ARMA\n", | |
"\n", | |
"arma = ARMA(X[X['t'] < N/2]['Y'].values, (5, 4))\n", | |
"result = arma.fit()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 62, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stderr", | |
"output_type": "stream", | |
"text": [ | |
"/home/akelleh/.virtualenvs/data/lib/python3.5/site-packages/statsmodels/tsa/kalmanf/kalmanfilter.py:577: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n", | |
" if issubdtype(paramsdtype, float):\n" | |
] | |
} | |
], | |
"source": [ | |
"X['y_pred'] = list(result.predict()) + list(result.predict(start=500, end=999))" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 64, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stderr", | |
"output_type": "stream", | |
"text": [ | |
"/home/akelleh/.virtualenvs/data/lib/python3.5/site-packages/pandas/plotting/_core.py:1716: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access\n", | |
" series.name = label\n" | |
] | |
}, | |
{ | |
"data": { | |
"text/plain": [ | |
"<matplotlib.axes._subplots.AxesSubplot at 0x7f67994fab38>" | |
] | |
}, | |
"execution_count": 64, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"X.plot(y=['y_pred', 'Y'], x='t')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 65, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"X['delta'] = X['Y'] - X['y_pred']" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 66, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"<matplotlib.axes._subplots.AxesSubplot at 0x7f67994c8a20>" | |
] | |
}, | |
"execution_count": 66, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"X.plot(y='delta', x='t')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 85, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"import matplotlib.pyplot as plt\n", | |
"\n", | |
"disaster_data = np.ma.masked_values([4, 5, 4, 0, 1, 4, 3, 4, 0, 6, 3, 3, 4, 0, 2, 6,\n", | |
" 3, 3, 5, 4, 5, 3, 1, 4, 4, 1, 5, 5, 3, 4, 2, 5,\n", | |
" 2, 2, 3, 4, 2, 1, 3, -999, 2, 1, 1, 1, 1, 3, 0, 0,\n", | |
" 1, 0, 1, 1, 0, 0, 3, 1, 0, 3, 2, 2, 0, 1, 1, 1,\n", | |
" 0, 1, 0, 1, 0, 0, 0, 2, 1, 0, 0, 0, 1, 1, 0, 2,\n", | |
" 3, 3, 1, -999, 2, 1, 1, 1, 1, 2, 4, 2, 0, 0, 1, 4,\n", | |
" 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1], value=-999)\n", | |
"year = np.arange(1851, 1962)\n", | |
"\n", | |
"plt.plot(year, disaster_data, 'o', markersize=8);\n", | |
"plt.ylabel(\"Disaster count\")\n", | |
"plt.xlabel(\"Year\");" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 87, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stderr", | |
"output_type": "stream", | |
"text": [ | |
"/home/akelleh/.virtualenvs/data/lib/python3.5/site-packages/pymc3/model.py:384: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n", | |
" if not np.issubdtype(var.dtype, float):\n", | |
"Multiprocess sampling (4 chains in 4 jobs)\n", | |
"CompoundStep\n", | |
">NUTS: [late_rate_log__, early_rate_log__]\n", | |
">CompoundStep\n", | |
">>Metropolis: [disasters_missing]\n", | |
">>Metropolis: [switchpoint]\n", | |
" 99%|█████████▉| 10416/10500 [00:07<00:00, 1369.66it/s]/home/akelleh/.virtualenvs/data/lib/python3.5/site-packages/numpy/core/fromnumeric.py:2957: RuntimeWarning: Mean of empty slice.\n", | |
" out=out, **kwargs)\n", | |
"100%|██████████| 10500/10500 [00:07<00:00, 1367.92it/s]\n", | |
"INFO (theano.gof.compilelock): Waiting for existing lock by process '6798' (I am process '6799')\n", | |
"INFO (theano.gof.compilelock): To manually release the lock, delete /home/akelleh/.theano/compiledir_Linux-4.13--generic-x86_64-with-Ubuntu-16.04-xenial-x86_64-3.5.2-64/lock_dir\n", | |
"INFO (theano.gof.compilelock): Waiting for existing lock by process '6798' (I am process '6800')\n", | |
"INFO (theano.gof.compilelock): To manually release the lock, delete /home/akelleh/.theano/compiledir_Linux-4.13--generic-x86_64-with-Ubuntu-16.04-xenial-x86_64-3.5.2-64/lock_dir\n", | |
"INFO (theano.gof.compilelock): Waiting for existing lock by process '6799' (I am process '6800')\n", | |
"INFO (theano.gof.compilelock): To manually release the lock, delete /home/akelleh/.theano/compiledir_Linux-4.13--generic-x86_64-with-Ubuntu-16.04-xenial-x86_64-3.5.2-64/lock_dir\n", | |
"/home/akelleh/.virtualenvs/data/lib/python3.5/site-packages/numpy/core/fromnumeric.py:2957: RuntimeWarning: Mean of empty slice.\n", | |
" out=out, **kwargs)\n", | |
"/home/akelleh/.virtualenvs/data/lib/python3.5/site-packages/numpy/core/fromnumeric.py:2957: RuntimeWarning: Mean of empty slice.\n", | |
" out=out, **kwargs)\n", | |
"/home/akelleh/.virtualenvs/data/lib/python3.5/site-packages/numpy/core/fromnumeric.py:2957: RuntimeWarning: Mean of empty slice.\n", | |
" out=out, **kwargs)\n", | |
"Tuning was enabled throughout the whole trace.\n", | |
"Tuning was enabled throughout the whole trace.\n", | |
"Tuning was enabled throughout the whole trace.\n", | |
"Tuning was enabled throughout the whole trace.\n", | |
"The number of effective samples is smaller than 10% for some parameters.\n" | |
] | |
} | |
], | |
"source": [ | |
"import pymc3 as pm\n", | |
"\n", | |
"with pm.Model() as disaster_model:\n", | |
"\n", | |
" switchpoint = pm.DiscreteUniform('switchpoint', lower=year.min(), upper=year.max(), testval=1900)\n", | |
"\n", | |
" # Priors for pre- and post-switch rates number of disasters\n", | |
" early_rate = pm.Exponential('early_rate', 1)\n", | |
" late_rate = pm.Exponential('late_rate', 1)\n", | |
"\n", | |
" # Allocate appropriate Poisson rates to years before and after current\n", | |
" rate = pm.math.switch(switchpoint >= year, early_rate, late_rate)\n", | |
"\n", | |
" disasters = pm.Poisson('disasters', rate, observed=disaster_data)\n", | |
" trace = pm.sample(10000)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 88, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f67b6362b00>,\n", | |
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f678439ae10>],\n", | |
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7f67843b5128>,\n", | |
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f678434d400>],\n", | |
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7f67843656d8>,\n", | |
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f67842fd9b0>],\n", | |
" [<matplotlib.axes._subplots.AxesSubplot object at 0x7f6784315c88>,\n", | |
" <matplotlib.axes._subplots.AxesSubplot object at 0x7f678432df60>]],\n", | |
" dtype=object)" | |
] | |
}, | |
"execution_count": 88, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 864x576 with 8 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"pm.traceplot(trace)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 115, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"N = 1000\n", | |
"\n", | |
"U = np.random.normal(size=N)\n", | |
"deltapp = np.random.normal(1., size=N)\n", | |
"Y80 = 98 + U + 0.1*np.random.normal(size=N)\n", | |
"Y90 = 99 + U + 0.1*np.random.normal(size=N)\n", | |
"Y100 = 100 + U + 0.1*np.random.normal(size=N)\n", | |
"\n", | |
"Y81 = Y80 + deltapp\n", | |
"Y91 = Y90 + deltapp\n", | |
"Y101 = Y100 + deltapp\n", | |
"D = np.random.binomial(1, p=1. / (1. + np.exp(-(U + deltapp))))\n" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 116, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"X = pd.DataFrame({'D': D, '$Y_8(0)$': Y80, '$Y_9(0)$': Y90, '$Y_{10}(0)$': Y100, \n", | |
" '$Y_8(1)$': Y81, '$Y_9(1)$': Y91, '$Y_{10}(1)$': Y101,})" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 117, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"X['$\\delta_8$'] = X['$Y_8(1)$'] - X['$Y_8(0)$']\n", | |
"X['$\\delta_9$'] = X['$Y_9(1)$'] - X['$Y_8(0)$']\n", | |
"X['$\\delta_{10}$'] = X['$Y_{10}(1)$'] - X['$Y_{10}(0)$']\n", | |
"\n", | |
"X['$Y_8$'] = X['D'] *X['$Y_8(1)$'] + (1-X['D'])* X['$Y_8(0)$']\n", | |
"X['$Y_9$'] = X['D'] *X['$Y_9(1)$'] + (1-X['D'])*X['$Y_8(0)$']\n", | |
"X['$Y_{10}$'] = X['D'] *X['$Y_{10}(1)$'] + (1-X['D'])*X['$Y_{10}(0)$']" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 118, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"$Y_8(0)$ 98.057990\n", | |
"$Y_8(1)$ 99.081647\n", | |
"$Y_9(0)$ 99.065797\n", | |
"$Y_9(1)$ 100.089455\n", | |
"$Y_{10}(0)$ 100.061053\n", | |
"$Y_{10}(1)$ 101.084711\n", | |
"D 0.675000\n", | |
"$\\delta_8$ 1.023657\n", | |
"$\\delta_9$ 2.031465\n", | |
"$\\delta_{10}$ 1.023657\n", | |
"$Y_8$ 98.883562\n", | |
"$Y_9$ 99.565636\n", | |
"$Y_{10}$ 100.886626\n", | |
"dtype: float64" | |
] | |
}, | |
"execution_count": 118, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"X.mean()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 119, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"X['change_score'] = X['$Y_9$'] - X['$Y_8$']" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 120, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"from statsmodels.api import OLS" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 124, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<table class=\"simpletable\">\n", | |
"<caption>OLS Regression Results</caption>\n", | |
"<tr>\n", | |
" <th>Dep. Variable:</th> <td>$Y_9$</td> <th> R-squared: </th> <td> 0.578</td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Model:</th> <td>OLS</td> <th> Adj. R-squared: </th> <td> 0.578</td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Method:</th> <td>Least Squares</td> <th> F-statistic: </th> <td> 1368.</td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Date:</th> <td>Thu, 29 Mar 2018</td> <th> Prob (F-statistic):</th> <td>2.78e-189</td>\n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Time:</th> <td>17:26:37</td> <th> Log-Likelihood: </th> <td> -1586.1</td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>No. Observations:</th> <td> 1000</td> <th> AIC: </th> <td> 3176.</td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Df Residuals:</th> <td> 998</td> <th> BIC: </th> <td> 3186.</td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Df Model:</th> <td> 1</td> <th> </th> <td> </td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Covariance Type:</th> <td>nonrobust</td> <th> </th> <td> </td> \n", | |
"</tr>\n", | |
"</table>\n", | |
"<table class=\"simpletable\">\n", | |
"<tr>\n", | |
" <td></td> <th>coef</th> <th>std err</th> <th>t</th> <th>P>|t|</th> <th>[0.025</th> <th>0.975]</th> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>D</th> <td> 2.9547</td> <td> 0.080</td> <td> 36.988</td> <td> 0.000</td> <td> 2.798</td> <td> 3.111</td>\n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>intercept</th> <td> 97.5712</td> <td> 0.066</td> <td> 1486.672</td> <td> 0.000</td> <td> 97.442</td> <td> 97.700</td>\n", | |
"</tr>\n", | |
"</table>\n", | |
"<table class=\"simpletable\">\n", | |
"<tr>\n", | |
" <th>Omnibus:</th> <td> 5.396</td> <th> Durbin-Watson: </th> <td> 2.030</td>\n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Prob(Omnibus):</th> <td> 0.067</td> <th> Jarque-Bera (JB): </th> <td> 5.397</td>\n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Skew:</th> <td> 0.143</td> <th> Prob(JB): </th> <td> 0.0673</td>\n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Kurtosis:</th> <td> 3.218</td> <th> Cond. No. </th> <td> 3.27</td>\n", | |
"</tr>\n", | |
"</table>" | |
], | |
"text/plain": [ | |
"<class 'statsmodels.iolib.summary.Summary'>\n", | |
"\"\"\"\n", | |
" OLS Regression Results \n", | |
"==============================================================================\n", | |
"Dep. Variable: $Y_9$ R-squared: 0.578\n", | |
"Model: OLS Adj. R-squared: 0.578\n", | |
"Method: Least Squares F-statistic: 1368.\n", | |
"Date: Thu, 29 Mar 2018 Prob (F-statistic): 2.78e-189\n", | |
"Time: 17:26:37 Log-Likelihood: -1586.1\n", | |
"No. Observations: 1000 AIC: 3176.\n", | |
"Df Residuals: 998 BIC: 3186.\n", | |
"Df Model: 1 \n", | |
"Covariance Type: nonrobust \n", | |
"==============================================================================\n", | |
" coef std err t P>|t| [0.025 0.975]\n", | |
"------------------------------------------------------------------------------\n", | |
"D 2.9547 0.080 36.988 0.000 2.798 3.111\n", | |
"intercept 97.5712 0.066 1486.672 0.000 97.442 97.700\n", | |
"==============================================================================\n", | |
"Omnibus: 5.396 Durbin-Watson: 2.030\n", | |
"Prob(Omnibus): 0.067 Jarque-Bera (JB): 5.397\n", | |
"Skew: 0.143 Prob(JB): 0.0673\n", | |
"Kurtosis: 3.218 Cond. No. 3.27\n", | |
"==============================================================================\n", | |
"\n", | |
"Warnings:\n", | |
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", | |
"\"\"\"" | |
] | |
}, | |
"execution_count": 124, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"X['intercept'] = 1.\n", | |
"\n", | |
"model = OLS(X['$Y_9$'], X[['D', 'intercept']])\n", | |
"result = model.fit()\n", | |
"result.summary()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 126, | |
"metadata": { | |
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{ | |
"data": { | |
"text/html": [ | |
"<table class=\"simpletable\">\n", | |
"<caption>OLS Regression Results</caption>\n", | |
"<tr>\n", | |
" <th>Dep. Variable:</th> <td>change_score</td> <th> R-squared: </th> <td> 0.947</td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Model:</th> <td>OLS</td> <th> Adj. R-squared: </th> <td> 0.947</td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Method:</th> <td>Least Squares</td> <th> F-statistic: </th> <td>1.789e+04</td>\n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Date:</th> <td>Thu, 29 Mar 2018</td> <th> Prob (F-statistic):</th> <td> 0.00</td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Time:</th> <td>17:26:55</td> <th> Log-Likelihood: </th> <td> 772.34</td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>No. Observations:</th> <td> 1000</td> <th> AIC: </th> <td> -1541.</td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Df Residuals:</th> <td> 998</td> <th> BIC: </th> <td> -1531.</td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Df Model:</th> <td> 1</td> <th> </th> <td> </td> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Covariance Type:</th> <td>nonrobust</td> <th> </th> <td> </td> \n", | |
"</tr>\n", | |
"</table>\n", | |
"<table class=\"simpletable\">\n", | |
"<tr>\n", | |
" <td></td> <th>coef</th> <th>std err</th> <th>t</th> <th>P>|t|</th> <th>[0.025</th> <th>0.975]</th> \n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>D</th> <td> 1.0105</td> <td> 0.008</td> <td> 133.766</td> <td> 0.000</td> <td> 0.996</td> <td> 1.025</td>\n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>intercept</th> <td>-2.104e-16</td> <td> 0.006</td> <td>-3.39e-14</td> <td> 1.000</td> <td> -0.012</td> <td> 0.012</td>\n", | |
"</tr>\n", | |
"</table>\n", | |
"<table class=\"simpletable\">\n", | |
"<tr>\n", | |
" <th>Omnibus:</th> <td>29.510</td> <th> Durbin-Watson: </th> <td> 2.006</td>\n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Prob(Omnibus):</th> <td> 0.000</td> <th> Jarque-Bera (JB): </th> <td> 68.309</td>\n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Skew:</th> <td> 0.053</td> <th> Prob(JB): </th> <td>1.47e-15</td>\n", | |
"</tr>\n", | |
"<tr>\n", | |
" <th>Kurtosis:</th> <td> 4.276</td> <th> Cond. No. </th> <td> 3.27</td>\n", | |
"</tr>\n", | |
"</table>" | |
], | |
"text/plain": [ | |
"<class 'statsmodels.iolib.summary.Summary'>\n", | |
"\"\"\"\n", | |
" OLS Regression Results \n", | |
"==============================================================================\n", | |
"Dep. Variable: change_score R-squared: 0.947\n", | |
"Model: OLS Adj. R-squared: 0.947\n", | |
"Method: Least Squares F-statistic: 1.789e+04\n", | |
"Date: Thu, 29 Mar 2018 Prob (F-statistic): 0.00\n", | |
"Time: 17:26:55 Log-Likelihood: 772.34\n", | |
"No. Observations: 1000 AIC: -1541.\n", | |
"Df Residuals: 998 BIC: -1531.\n", | |
"Df Model: 1 \n", | |
"Covariance Type: nonrobust \n", | |
"==============================================================================\n", | |
" coef std err t P>|t| [0.025 0.975]\n", | |
"------------------------------------------------------------------------------\n", | |
"D 1.0105 0.008 133.766 0.000 0.996 1.025\n", | |
"intercept -2.104e-16 0.006 -3.39e-14 1.000 -0.012 0.012\n", | |
"==============================================================================\n", | |
"Omnibus: 29.510 Durbin-Watson: 2.006\n", | |
"Prob(Omnibus): 0.000 Jarque-Bera (JB): 68.309\n", | |
"Skew: 0.053 Prob(JB): 1.47e-15\n", | |
"Kurtosis: 4.276 Cond. No. 3.27\n", | |
"==============================================================================\n", | |
"\n", | |
"Warnings:\n", | |
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", | |
"\"\"\"" | |
] | |
}, | |
"execution_count": 126, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"X['intercept'] = 1.\n", | |
"\n", | |
"model = OLS(X['change_score'], X[['D', 'intercept']])\n", | |
"result = model.fit()\n", | |
"result.summary()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": {}, | |
"outputs": [], | |
"source": [] | |
}, | |
{ | |
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} | |
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