{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Robust Linear Models" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:56.720978Z", "iopub.status.busy": "2022-11-02T17:06:56.720457Z", "iopub.status.idle": "2022-11-02T17:06:57.217444Z", "shell.execute_reply": "2022-11-02T17:06:57.216805Z" } }, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:57.222570Z", "iopub.status.busy": "2022-11-02T17:06:57.221153Z", "iopub.status.idle": "2022-11-02T17:06:57.976837Z", "shell.execute_reply": "2022-11-02T17:06:57.976134Z" } }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import statsmodels.api as sm" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Estimation\n", "\n", "Load data:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:57.982501Z", "iopub.status.busy": "2022-11-02T17:06:57.981192Z", "iopub.status.idle": "2022-11-02T17:06:57.991449Z", "shell.execute_reply": "2022-11-02T17:06:57.990907Z" } }, "outputs": [], "source": [ "data = sm.datasets.stackloss.load()\n", "data.exog = sm.add_constant(data.exog)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Huber's T norm with the (default) median absolute deviation scaling" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:57.995965Z", "iopub.status.busy": "2022-11-02T17:06:57.994866Z", "iopub.status.idle": "2022-11-02T17:06:58.012895Z", "shell.execute_reply": "2022-11-02T17:06:58.012347Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "const -41.026498\n", "AIRFLOW 0.829384\n", "WATERTEMP 0.926066\n", "ACIDCONC -0.127847\n", "dtype: float64\n", "const 9.791899\n", "AIRFLOW 0.111005\n", "WATERTEMP 0.302930\n", "ACIDCONC 0.128650\n", "dtype: float64\n", " Robust linear Model Regression Results \n", "==============================================================================\n", "Dep. Variable: y No. Observations: 21\n", "Model: RLM Df Residuals: 17\n", "Method: IRLS Df Model: 3\n", "Norm: HuberT \n", "Scale Est.: mad \n", "Cov Type: H1 \n", "Date: Wed, 02 Nov 2022 \n", "Time: 17:06:58 \n", "No. Iterations: 19 \n", "==============================================================================\n", " coef std err z P>|z| [0.025 0.975]\n", "------------------------------------------------------------------------------\n", "var_0 -41.0265 9.792 -4.190 0.000 -60.218 -21.835\n", "var_1 0.8294 0.111 7.472 0.000 0.612 1.047\n", "var_2 0.9261 0.303 3.057 0.002 0.332 1.520\n", "var_3 -0.1278 0.129 -0.994 0.320 -0.380 0.124\n", "==============================================================================\n", "\n", "If the model instance has been used for another fit with different fit parameters, then the fit options might not be the correct ones anymore .\n" ] } ], "source": [ "huber_t = sm.RLM(data.endog, data.exog, M=sm.robust.norms.HuberT())\n", "hub_results = huber_t.fit()\n", "print(hub_results.params)\n", "print(hub_results.bse)\n", "print(\n", " hub_results.summary(\n", " yname=\"y\", xname=[\"var_%d\" % i for i in range(len(hub_results.params))]\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Huber's T norm with 'H2' covariance matrix" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:58.017389Z", "iopub.status.busy": "2022-11-02T17:06:58.016287Z", "iopub.status.idle": "2022-11-02T17:06:58.033885Z", "shell.execute_reply": "2022-11-02T17:06:58.033347Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "const -41.026498\n", "AIRFLOW 0.829384\n", "WATERTEMP 0.926066\n", "ACIDCONC -0.127847\n", "dtype: float64\n", "const 9.089504\n", "AIRFLOW 0.119460\n", "WATERTEMP 0.322355\n", "ACIDCONC 0.117963\n", "dtype: float64\n" ] } ], "source": [ "hub_results2 = huber_t.fit(cov=\"H2\")\n", "print(hub_results2.params)\n", "print(hub_results2.bse)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Andrew's Wave norm with Huber's Proposal 2 scaling and 'H3' covariance matrix" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:58.039562Z", "iopub.status.busy": "2022-11-02T17:06:58.037888Z", "iopub.status.idle": "2022-11-02T17:06:58.094927Z", "shell.execute_reply": "2022-11-02T17:06:58.094193Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Parameters: const -40.881796\n", "AIRFLOW 0.792761\n", "WATERTEMP 1.048576\n", "ACIDCONC -0.133609\n", "dtype: float64\n" ] } ], "source": [ "andrew_mod = sm.RLM(data.endog, data.exog, M=sm.robust.norms.AndrewWave())\n", "andrew_results = andrew_mod.fit(scale_est=sm.robust.scale.HuberScale(), cov=\"H3\")\n", "print(\"Parameters: \", andrew_results.params)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "See ``help(sm.RLM.fit)`` for more options and ``module sm.robust.scale`` for scale options\n", "\n", "## Comparing OLS and RLM\n", "\n", "Artificial data with outliers:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:58.098625Z", "iopub.status.busy": "2022-11-02T17:06:58.098234Z", "iopub.status.idle": "2022-11-02T17:06:58.103689Z", "shell.execute_reply": "2022-11-02T17:06:58.102939Z" } }, "outputs": [], "source": [ "nsample = 50\n", "x1 = np.linspace(0, 20, nsample)\n", "X = np.column_stack((x1, (x1 - 5) ** 2))\n", "X = sm.add_constant(X)\n", "sig = 0.3 # smaller error variance makes OLS<->RLM contrast bigger\n", "beta = [5, 0.5, -0.0]\n", "y_true2 = np.dot(X, beta)\n", "y2 = y_true2 + sig * 1.0 * np.random.normal(size=nsample)\n", "y2[[39, 41, 43, 45, 48]] -= 5 # add some outliers (10% of nsample)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Example 1: quadratic function with linear truth\n", "\n", "Note that the quadratic term in OLS regression will capture outlier effects. " ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:58.106812Z", "iopub.status.busy": "2022-11-02T17:06:58.106482Z", "iopub.status.idle": "2022-11-02T17:06:58.117783Z", "shell.execute_reply": "2022-11-02T17:06:58.117119Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 4.78516573 0.55123012 -0.01444285]\n", "[0.44525161 0.06874084 0.0060825 ]\n", "[ 4.42409451 4.70563066 4.98235453 5.25426612 5.52136544 5.78365248\n", " 6.04112723 6.29378972 6.54163992 6.78467784 7.02290349 7.25631686\n", " 7.48491795 7.70870677 7.92768331 8.14184756 8.35119955 8.55573925\n", " 8.75546667 8.95038182 9.14048469 9.32577528 9.5062536 9.68191964\n", " 9.85277339 10.01881488 10.18004408 10.336461 10.48806565 10.63485802\n", " 10.77683811 10.91400593 11.04636146 11.17390472 11.2966357 11.41455441\n", " 11.52766083 11.63595498 11.73943685 11.83810644 11.93196376 12.02100879\n", " 12.10524155 12.18466203 12.25927024 12.32906616 12.39404981 12.45422118\n", " 12.50958027 12.56012709]\n" ] } ], "source": [ "res = sm.OLS(y2, X).fit()\n", "print(res.params)\n", "print(res.bse)\n", "print(res.predict())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Estimate RLM:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:58.121156Z", "iopub.status.busy": "2022-11-02T17:06:58.120793Z", "iopub.status.idle": "2022-11-02T17:06:58.143223Z", "shell.execute_reply": "2022-11-02T17:06:58.142552Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 4.68933411e+00 5.38229820e-01 -3.74367086e-03]\n", "[0.11236366 0.01734743 0.00153498]\n" ] } ], "source": [ "resrlm = sm.RLM(y2, X).fit()\n", "print(resrlm.params)\n", "print(resrlm.bse)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Draw a plot to compare OLS estimates to the robust estimates:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:58.146706Z", "iopub.status.busy": "2022-11-02T17:06:58.146332Z", "iopub.status.idle": "2022-11-02T17:06:58.404307Z", "shell.execute_reply": "2022-11-02T17:06:58.403678Z" } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(12, 8))\n", "ax = fig.add_subplot(111)\n", "ax.plot(x1, y2, \"o\", label=\"data\")\n", "ax.plot(x1, y_true2, \"b-\", label=\"True\")\n", "pred_ols = res.get_prediction()\n", "iv_l = pred_ols.summary_frame()[\"obs_ci_lower\"]\n", "iv_u = pred_ols.summary_frame()[\"obs_ci_upper\"]\n", "\n", "ax.plot(x1, res.fittedvalues, \"r-\", label=\"OLS\")\n", "ax.plot(x1, iv_u, \"r--\")\n", "ax.plot(x1, iv_l, \"r--\")\n", "ax.plot(x1, resrlm.fittedvalues, \"g.-\", label=\"RLM\")\n", "ax.legend(loc=\"best\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Example 2: linear function with linear truth\n", "\n", "Fit a new OLS model using only the linear term and the constant:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:58.407917Z", "iopub.status.busy": "2022-11-02T17:06:58.407558Z", "iopub.status.idle": "2022-11-02T17:06:58.412964Z", "shell.execute_reply": "2022-11-02T17:06:58.412420Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[5.36730096 0.40680163]\n", "[0.38922146 0.03353689]\n" ] } ], "source": [ "X2 = X[:, [0, 1]]\n", "res2 = sm.OLS(y2, X2).fit()\n", "print(res2.params)\n", "print(res2.bse)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Estimate RLM:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:58.416036Z", "iopub.status.busy": "2022-11-02T17:06:58.415658Z", "iopub.status.idle": "2022-11-02T17:06:58.423732Z", "shell.execute_reply": "2022-11-02T17:06:58.423194Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[4.82751717 0.50304602]\n", "[0.09082931 0.00782622]\n" ] } ], "source": [ "resrlm2 = sm.RLM(y2, X2).fit()\n", "print(resrlm2.params)\n", "print(resrlm2.bse)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Draw a plot to compare OLS estimates to the robust estimates:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2022-11-02T17:06:58.427955Z", "iopub.status.busy": "2022-11-02T17:06:58.426630Z", "iopub.status.idle": "2022-11-02T17:06:58.688797Z", "shell.execute_reply": "2022-11-02T17:06:58.688156Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pred_ols = res2.get_prediction()\n", "iv_l = pred_ols.summary_frame()[\"obs_ci_lower\"]\n", "iv_u = pred_ols.summary_frame()[\"obs_ci_upper\"]\n", "\n", "fig, ax = plt.subplots(figsize=(8, 6))\n", "ax.plot(x1, y2, \"o\", label=\"data\")\n", "ax.plot(x1, y_true2, \"b-\", label=\"True\")\n", "ax.plot(x1, res2.fittedvalues, \"r-\", label=\"OLS\")\n", "ax.plot(x1, iv_u, \"r--\")\n", "ax.plot(x1, iv_l, \"r--\")\n", "ax.plot(x1, resrlm2.fittedvalues, \"g.-\", label=\"RLM\")\n", "legend = ax.legend(loc=\"best\")" ] } ], "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": "3.10.8" } }, "nbformat": 4, "nbformat_minor": 4 }