{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# SARIMAX: Model selection, missing data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The example mirrors Durbin and Koopman (2012), Chapter 8.4 in application of Box-Jenkins methodology to fit ARMA models. The novel feature is the ability of the model to work on datasets with missing values." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2023-12-14T14:40:02.049336Z", "iopub.status.busy": "2023-12-14T14:40:02.049079Z", "iopub.status.idle": "2023-12-14T14:40:03.457396Z", "shell.execute_reply": "2023-12-14T14:40:03.456372Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2023-12-14T14:40:03.461857Z", "iopub.status.busy": "2023-12-14T14:40:03.460942Z", "iopub.status.idle": "2023-12-14T14:40:05.756186Z", "shell.execute_reply": "2023-12-14T14:40:05.755421Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "from scipy.stats import norm\n", "import statsmodels.api as sm\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2023-12-14T14:40:05.760047Z", "iopub.status.busy": "2023-12-14T14:40:05.759570Z", "iopub.status.idle": "2023-12-14T14:40:06.141476Z", "shell.execute_reply": "2023-12-14T14:40:06.140582Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [], "source": [ "import requests\n", "from io import BytesIO\n", "from zipfile import ZipFile\n", "\n", "# Download the dataset\n", "df = pd.read_table(\n", " \"https://raw.githubusercontent.com/jrnold/ssmodels-in-stan/master/StanStateSpace/data-raw/DK-data/internet.dat\",\n", " skiprows=1, header=None, sep='\\s+', engine='python',\n", " names=['internet','dinternet']\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model Selection\n", "\n", "As in Durbin and Koopman, we force a number of the values to be missing." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2023-12-14T14:40:06.145786Z", "iopub.status.busy": "2023-12-14T14:40:06.145437Z", "iopub.status.idle": "2023-12-14T14:40:06.151325Z", "shell.execute_reply": "2023-12-14T14:40:06.149981Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [], "source": [ "# Get the basic series\n", "dta_full = df.dinternet[1:].values\n", "dta_miss = dta_full.copy()\n", "\n", "# Remove datapoints\n", "missing = np.r_[6,16,26,36,46,56,66,72,73,74,75,76,86,96]-1\n", "dta_miss[missing] = np.nan" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Then we can consider model selection using the Akaike information criteria (AIC), but running the model for each variant and selecting the model with the lowest AIC value.\n", "\n", "There are a couple of things to note here:\n", "\n", "- When running such a large batch of models, particularly when the autoregressive and moving average orders become large, there is the possibility of poor maximum likelihood convergence. Below we ignore the warnings since this example is illustrative.\n", "- We use the option `enforce_invertibility=False`, which allows the moving average polynomial to be non-invertible, so that more of the models are estimable.\n", "- Several of the models do not produce good results, and their AIC value is set to NaN. This is not surprising, as Durbin and Koopman note numerical problems with the high order models." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2023-12-14T14:40:06.154489Z", "iopub.status.busy": "2023-12-14T14:40:06.154228Z", "iopub.status.idle": "2023-12-14T14:40:45.316581Z", "shell.execute_reply": "2023-12-14T14:40:45.315297Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [], "source": [ "import warnings\n", "\n", "aic_full = pd.DataFrame(np.zeros((6,6), dtype=float))\n", "aic_miss = pd.DataFrame(np.zeros((6,6), dtype=float))\n", "\n", "warnings.simplefilter('ignore')\n", "\n", "# Iterate over all ARMA(p,q) models with p,q in [0,6]\n", "for p in range(6):\n", " for q in range(6):\n", " if p == 0 and q == 0:\n", " continue\n", " \n", " # Estimate the model with no missing datapoints\n", " mod = sm.tsa.statespace.SARIMAX(dta_full, order=(p,0,q), enforce_invertibility=False)\n", " try:\n", " res = mod.fit(disp=False)\n", " aic_full.iloc[p,q] = res.aic\n", " except:\n", " aic_full.iloc[p,q] = np.nan\n", " \n", " # Estimate the model with missing datapoints\n", " mod = sm.tsa.statespace.SARIMAX(dta_miss, order=(p,0,q), enforce_invertibility=False)\n", " try:\n", " res = mod.fit(disp=False)\n", " aic_miss.iloc[p,q] = res.aic\n", " except:\n", " aic_miss.iloc[p,q] = np.nan" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For the models estimated over the full (non-missing) dataset, the AIC chooses ARMA(1,1) or ARMA(3,0). Durbin and Koopman suggest the ARMA(1,1) specification is better due to parsimony.\n", "\n", "$$\n", "\\text{Replication of:}\\\\\n", "\\textbf{Table 8.1} ~~ \\text{AIC for different ARMA models.}\\\\\n", "\\newcommand{\\r}[1]{{\\color{red}{#1}}}\n", "\\begin{array}{lrrrrrr}\n", "\\hline\n", "q & 0 & 1 & 2 & 3 & 4 & 5 \\\\\n", "\\hline\n", "p & {} & {} & {} & {} & {} & {} \\\\\n", "0 & 0.00 & 549.81 & 519.87 & 520.27 & 519.38 & 518.86 \\\\\n", "1 & 529.24 & \\r{514.30} & 516.25 & 514.58 & 515.10 & 516.28 \\\\\n", "2 & 522.18 & 516.29 & 517.16 & 515.77 & 513.24 & 514.73 \\\\\n", "3 & \\r{511.99} & 513.94 & 515.92 & 512.06 & 513.72 & 514.50 \\\\\n", "4 & 513.93 & 512.89 & nan & nan & 514.81 & 516.08 \\\\\n", "5 & 515.86 & 517.64 & nan & nan & nan & nan \\\\\n", "\\hline\n", "\\end{array}\n", "$$\n", "\n", "For the models estimated over missing dataset, the AIC chooses ARMA(1,1)\n", "\n", "$$\n", "\\text{Replication of:}\\\\\n", "\\textbf{Table 8.2} ~~ \\text{AIC for different ARMA models with missing observations.}\\\\\n", "\\begin{array}{lrrrrrr}\n", "\\hline\n", "q & 0 & 1 & 2 & 3 & 4 & 5 \\\\\n", "\\hline\n", "p & {} & {} & {} & {} & {} & {} \\\\\n", "0 & 0.00 & 488.93 & 464.01 & 463.86 & 462.63 & 463.62 \\\\\n", "1 & 468.01 & \\r{457.54} & 459.35 & 458.66 & 459.15 & 461.01 \\\\\n", "2 & 469.68 & nan & 460.48 & 459.43 & 459.23 & 460.47 \\\\\n", "3 & 467.10 & 458.44 & 459.64 & 456.66 & 459.54 & 460.05 \\\\\n", "4 & 469.00 & 459.52 & nan & 463.04 & 459.35 & 460.96 \\\\\n", "5 & 471.32 & 461.26 & nan & nan & 461.00 & 462.97 \\\\\n", "\\hline\n", "\\end{array}\n", "$$\n", "\n", "**Note**: the AIC values are calculated differently than in Durbin and Koopman, but show overall similar trends." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Postestimation\n", "\n", "Using the ARMA(1,1) specification selected above, we perform in-sample prediction and out-of-sample forecasting." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2023-12-14T14:40:45.320665Z", "iopub.status.busy": "2023-12-14T14:40:45.320392Z", "iopub.status.idle": "2023-12-14T14:40:45.458412Z", "shell.execute_reply": "2023-12-14T14:40:45.457206Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " SARIMAX Results \n", "==============================================================================\n", "Dep. Variable: y No. Observations: 99\n", "Model: SARIMAX(1, 0, 1) Log Likelihood -225.770\n", "Date: Thu, 14 Dec 2023 AIC 457.541\n", "Time: 14:40:45 BIC 465.326\n", "Sample: 0 HQIC 460.691\n", " - 99 \n", "Covariance Type: opg \n", "==============================================================================\n", " coef std err z P>|z| [0.025 0.975]\n", "------------------------------------------------------------------------------\n", "ar.L1 0.6562 0.092 7.125 0.000 0.476 0.837\n", "ma.L1 0.4878 0.111 4.390 0.000 0.270 0.706\n", "sigma2 10.3402 1.569 6.591 0.000 7.265 13.415\n", "===================================================================================\n", "Ljung-Box (L1) (Q): 0.00 Jarque-Bera (JB): 1.87\n", "Prob(Q): 0.96 Prob(JB): 0.39\n", "Heteroskedasticity (H): 0.59 Skew: -0.10\n", "Prob(H) (two-sided): 0.13 Kurtosis: 3.64\n", "===================================================================================\n", "\n", "Warnings:\n", "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n" ] } ], "source": [ "# Statespace\n", "mod = sm.tsa.statespace.SARIMAX(dta_miss, order=(1,0,1))\n", "res = mod.fit(disp=False)\n", "print(res.summary())" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2023-12-14T14:40:45.466201Z", "iopub.status.busy": "2023-12-14T14:40:45.462935Z", "iopub.status.idle": "2023-12-14T14:40:46.526700Z", "shell.execute_reply": "2023-12-14T14:40:46.525833Z" }, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# In-sample one-step-ahead predictions, and out-of-sample forecasts\n", "nforecast = 20\n", "predict = res.get_prediction(end=mod.nobs + nforecast)\n", "idx = np.arange(len(predict.predicted_mean))\n", "predict_ci = predict.conf_int(alpha=0.5)\n", "\n", "# Graph\n", "fig, ax = plt.subplots(figsize=(12,6))\n", "ax.xaxis.grid()\n", "ax.plot(dta_miss, 'k.')\n", "\n", "# Plot\n", "ax.plot(idx[:-nforecast], predict.predicted_mean[:-nforecast], 'gray')\n", "ax.plot(idx[-nforecast:], predict.predicted_mean[-nforecast:], 'k--', linestyle='--', linewidth=2)\n", "ax.fill_between(idx, predict_ci[:, 0], predict_ci[:, 1], alpha=0.15)\n", "\n", "ax.set(title='Figure 8.9 - Internet series');" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.10.13" } }, "nbformat": 4, "nbformat_minor": 4 }