com.opengamma.strata.math.impl.regression.WeightedLeastSquaresRegressionTest.java Source code

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Here is the source code for com.opengamma.strata.math.impl.regression.WeightedLeastSquaresRegressionTest.java

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/**
 * Copyright (C) 2009 - present by OpenGamma Inc. and the OpenGamma group of companies
 * 
 * Please see distribution for license.
 */
package com.opengamma.strata.math.impl.regression;

import static org.testng.AssertJUnit.assertEquals;

import org.apache.commons.math3.random.Well44497b;
import org.testng.Assert;
import org.testng.annotations.Test;

/**
 * Test.
 */
@Test
public class WeightedLeastSquaresRegressionTest {

    private static final Well44497b RANDOM = new Well44497b(0L);
    private static final double EPS = 1e-2;

    @Test
    public void test() {
        final double a0 = 2.3;
        final double a1 = -4.5;
        final double a2 = 0.76;
        final double a3 = 3.4;
        final int n = 30;
        final double[][] x = new double[n][3];
        final double[] yIntercept = new double[n];
        final double[] yNoIntercept = new double[n];
        final double[][] w1 = new double[n][n];
        final double[] w2 = new double[n];
        double y, x1, x2, x3;
        for (int i = 0; i < n; i++) {
            x1 = i;
            x2 = x1 * x1;
            x3 = Math.sqrt(x1);
            x[i] = new double[] { x1, x2, x3 };
            y = x1 * a1 + x2 * a2 + x3 * a3;
            yNoIntercept[i] = y;
            yIntercept[i] = y + a0;
            for (int j = 0; j < n; j++) {
                w1[i][j] = RANDOM.nextDouble();
            }
            w1[i][i] = 1.;
            w2[i] = 1.;
        }
        final WeightedLeastSquaresRegression wlsRegression = new WeightedLeastSquaresRegression();
        final OrdinaryLeastSquaresRegression olsRegression = new OrdinaryLeastSquaresRegression();
        try {
            wlsRegression.regress(x, (double[]) null, yNoIntercept, false);
            Assert.fail();
        } catch (final IllegalArgumentException e) {
            // Expected
        }
        LeastSquaresRegressionResult wls = wlsRegression.regress(x, w1, yIntercept, true);
        LeastSquaresRegressionResult ols = olsRegression.regress(x, yIntercept, true);
        assertRegressions(n, 4, wls, ols);
        wls = wlsRegression.regress(x, w1, yNoIntercept, false);
        ols = olsRegression.regress(x, yNoIntercept, false);
        assertRegressions(n, 3, wls, ols);
        wls = wlsRegression.regress(x, w2, yIntercept, true);
        ols = olsRegression.regress(x, yIntercept, true);
        assertRegressions(n, 4, wls, ols);
        wls = wlsRegression.regress(x, w2, yNoIntercept, false);
        ols = olsRegression.regress(x, yNoIntercept, false);
        assertRegressions(n, 3, wls, ols);
    }

    private void assertRegressions(final int n, final int k, final LeastSquaresRegressionResult regression1,
            final LeastSquaresRegressionResult regression2) {
        final double[] r1 = regression1.getResiduals();
        final double[] r2 = regression2.getResiduals();
        for (int i = 0; i < n; i++) {
            assertEquals(r1[i], r2[i], EPS);
        }
        final double[] b1 = regression1.getBetas();
        final double[] t1 = regression1.getTStatistics();
        final double[] p1 = regression1.getPValues();
        final double[] s1 = regression1.getStandardErrorOfBetas();
        final double[] b2 = regression2.getBetas();
        final double[] t2 = regression2.getTStatistics();
        final double[] p2 = regression2.getPValues();
        final double[] s2 = regression2.getStandardErrorOfBetas();
        for (int i = 0; i < k; i++) {
            assertEquals(b1[i], b2[i], EPS);
            assertEquals(t1[i], t2[i], EPS);
            assertEquals(p1[i], p2[i], EPS);
            assertEquals(s1[i], s2[i], EPS);
        }
        assertEquals(regression1.getRSquared(), regression2.getRSquared(), EPS);
        assertEquals(regression1.getAdjustedRSquared(), regression2.getAdjustedRSquared(), EPS);
        assertEquals(regression1.getMeanSquareError(), regression2.getMeanSquareError(), EPS);
    }
}