package com.imsl.test.example.stat;

import com.imsl.stat.*;
import java.util.*;

/**
 * <p>
 * Performs outlier identification and simultaneously 
 * fits an \(\text{ARIMA}(2,2,0)\) to the Canadian Lynx dataset.</p>
 * <p>
 * The data is a time series of the estimated population of Canadian lynx.
 * Class <code>ARMAOutlierIdentification</code> is used to fit an
 * \(\text{ARIMA}(2,2,0)\) model of the form
 * \((1-B)(1-\phi_1B-\phi_2B^2)Y_t=a_t,\, t=1,2,\ldots,144,\,\) where \( \{a_t\}\) 
 * is Gaussian white noise. 
 *  The  <code>compute</code> method determines the estimates
 *  \(\hat{\phi}_1=0.10682\) and \(\hat{\phi}_2=-0.19666\) and identifies a 
 * level shift (LS) type outlier at time point \(t=16\).
 * </p>
 *
 * @see <a href="ARMAOutlierIdentificationEx1.java">Code</a>
 * @see <a href="doc-files/ARMAOutlierIdentificationEx1.out">Output</a>
 */
public class ARMAOutlierIdentificationEx1 {

    public static void main(String args[]) throws Exception {
        double[] series = {
            0.24300E01, 0.25060E01, 0.27670E01, 0.29400E01, 0.31690E01,
            0.34500E01, 0.35940E01, 0.37740E01, 0.36950E01, 0.34110E01,
            0.27180E01, 0.19910E01, 0.22650E01, 0.24460E01, 0.26120E01,
            0.33590E01, 0.34290E01, 0.35330E01, 0.32610E01, 0.26120E01,
            0.21790E01, 0.16530E01, 0.18320E01, 0.23280E01, 0.27370E01,
            0.30140E01, 0.33280E01, 0.34040E01, 0.29810E01, 0.25570E01,
            0.25760E01, 0.23520E01, 0.25560E01, 0.28640E01, 0.32140E01,
            0.34350E01, 0.34580E01, 0.33260E01, 0.28350E01, 0.24760E01,
            0.23730E01, 0.23890E01, 0.27420E01, 0.32100E01, 0.35200E01,
            0.38280E01, 0.36280E01, 0.28370E01, 0.24060E01, 0.26750E01,
            0.25540E01, 0.28940E01, 0.32020E01, 0.32240E01, 0.33520E01,
            0.31540E01, 0.28780E01, 0.24760E01, 0.23030E01, 0.23600E01,
            0.26710E01, 0.28670E01, 0.33100E01, 0.34490E01, 0.36460E01,
            0.34000E01, 0.25900E01, 0.18630E01, 0.15810E01, 0.16900E01,
            0.17710E01, 0.22740E01, 0.25760E01, 0.31110E01, 0.36050E01,
            0.35430E01, 0.27690E01, 0.20210E01, 0.21850E01, 0.25880E01,
            0.28800E01, 0.31150E01, 0.35400E01, 0.38450E01, 0.38000E01,
            0.35790E01, 0.32640E01, 0.25380E01, 0.25820E01, 0.29070E01,
            0.31420E01, 0.34330E01, 0.35800E01, 0.34900E01, 0.34750E01,
            0.35790E01, 0.28290E01, 0.19090E01, 0.19030E01, 0.20330E01,
            0.23600E01, 0.26010E01, 0.30540E01, 0.33860E01, 0.35530E01,
            0.34680E01, 0.31870E01, 0.27230E01, 0.26860E01, 0.28210E01,
            0.30000E01, 0.32010E01, 0.34240E01, 0.35310E01
        };

        int[] model = new int[4];
        double[] outlierFreeSeries;
        double resStdErr, aic, constant;
        double[] ar;
        int[][] outlierStatistics;
        int numOutliers;

        model[0] = 2;
        model[1] = 0;
        model[2] = 1;
        model[3] = 2;

        ARMAOutlierIdentification armaOutlier
                = new ARMAOutlierIdentification(series);

        armaOutlier.setCriticalValue(3.5);
        armaOutlier.compute(model);

        outlierFreeSeries = armaOutlier.getOutlierFreeSeries();
        numOutliers = armaOutlier.getNumberOfOutliers();
        outlierStatistics = armaOutlier.getOutlierStatistics();
        constant = armaOutlier.getConstant();
        ar = armaOutlier.getAR();
        resStdErr = armaOutlier.getResidualStandardError();
        aic = armaOutlier.getAIC();

        System.out.printf("%n%n   ARMA parameters:%n");
        System.out.printf(Locale.ENGLISH, "constant:%9.6f%n", constant);
        System.out.printf(Locale.ENGLISH, "ar[0]:%12.6f%n", ar[0]);
        System.out.printf(Locale.ENGLISH, "ar[1]:%12.6f%n%n", ar[1]);
        System.out.printf("Number of outliers:%3d%n", numOutliers);
        System.out.printf("%n   Outlier statistics:%n");
        System.out.printf("Time point%6sOutlier type%n", " ");
        for (int i = 0; i < numOutliers; i++) {
            System.out.printf("%10d%18d%n", outlierStatistics[i][0],
                    outlierStatistics[i][1]);
        }
        System.out.printf(Locale.ENGLISH, "%nRSE:%9.6f%n", resStdErr);
        System.out.printf(Locale.ENGLISH, "AIC:%11.6f", aic);
        System.out.printf("%n%n   Extract from the series:%n");
        System.out.printf("time   original   outlier free%n");
        for (int i = 0; i < 36; i++) {
            System.out.printf(Locale.ENGLISH, "%4d%11.4f%15.4f%n",
                    i + 1, series[i], outlierFreeSeries[i]);
        }
    }
}