Examples of ChiSquareTest

org.apache.commons.math.stat.inference.ChiSquareTest
An interface for Chi-Square tests.
This interface handles only known distributions. If the distribution is unknown and should be provided by a sample, then the {@link UnknownDistributionChiSquareTest UnknownDistributionChiSquareTest} extended interface should be used instead.
@version $Revision: 811685 $ $Date: 2009-09-05 19:36:48 +0200 (sam. 05 sept. 2009) $
org.apache.commons.math3.stat.inference.ChiSquareTest
Implements Chi-Square test statistics.
This implementation handles both known and unknown distributions.

Two samples tests can be used when the distribution is unknown a priori but provided by one sample, or when the hypothesis under test is that the two samples come from the same underlying distribution.

Examples of org.apache.commons.math3.stat.inference.ChiSquareTest

     * @param expected expected counts
     * @param observed observed counts
     * @param alpha significance level of the test
     */
    public static void assertChiSquareAccept(String[] valueLabels, double[] expected, long[] observed, double alpha) {
        ChiSquareTest chiSquareTest = new ChiSquareTest();


        // Fail if we can reject null hypothesis that distributions are the same
        if (chiSquareTest.chiSquareTest(expected, observed, alpha)) {
            StringBuilder msgBuffer = new StringBuilder();
            DecimalFormat df = new DecimalFormat("#.##");
            msgBuffer.append("Chisquare test failed");
            msgBuffer.append(" p-value = ");
            msgBuffer.append(chiSquareTest.chiSquareTest(expected, observed));
            msgBuffer.append(" chisquare statistic = ");
            msgBuffer.append(chiSquareTest.chiSquare(expected, observed));
            msgBuffer.append(". \n");
            msgBuffer.append("value\texpected\tobserved\n");
            for (int i = 0; i < expected.length; i++) {
                msgBuffer.append(valueLabels[i]);
                msgBuffer.append("\t");

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Examples of org.apache.commons.math3.stat.inference.ChiSquareTest

            expected[i] = (poissonDistribution.cumulativeProbability(binBounds.get(i) - 1) -
                poissonDistribution.cumulativeProbability(binBounds.get(i - 1) -1)) * sampleSize;
        }


        // Use chisquare test to verify that generated values are poisson(mean)-distributed
        ChiSquareTest chiSquareTest = new ChiSquareTest();
            // Fail if we can reject null hypothesis that distributions are the same
        if (chiSquareTest.chiSquareTest(expected, observed, alpha)) {
            StringBuilder msgBuffer = new StringBuilder();
            DecimalFormat df = new DecimalFormat("#.##");
            msgBuffer.append("Chisquare test failed for mean = ");
            msgBuffer.append(mean);
            msgBuffer.append(" p-value = ");
            msgBuffer.append(chiSquareTest.chiSquareTest(expected, observed));
            msgBuffer.append(" chisquare statistic = ");
            msgBuffer.append(chiSquareTest.chiSquare(expected, observed));
            msgBuffer.append(". \n");
            msgBuffer.append("bin\t\texpected\tobserved\n");
            for (int i = 0; i < expected.length; i++) {
                msgBuffer.append("[");
                msgBuffer.append(i == 0 ? 1: binBounds.get(i - 1));

View Full Code Here

Examples of org.apache.commons.math3.stat.inference.ChiSquareTest

     * @param expected expected counts
     * @param observed observed counts
     * @param alpha significance level of the test
     */
    public static void assertChiSquareAccept(String[] valueLabels, double[] expected, long[] observed, double alpha) throws Exception {
        ChiSquareTest chiSquareTest = new ChiSquareTest();


        // Fail if we can reject null hypothesis that distributions are the same
        if (chiSquareTest.chiSquareTest(expected, observed, alpha)) {
            StringBuilder msgBuffer = new StringBuilder();
            DecimalFormat df = new DecimalFormat("#.##");
            msgBuffer.append("Chisquare test failed");
            msgBuffer.append(" p-value = ");
            msgBuffer.append(chiSquareTest.chiSquareTest(expected, observed));
            msgBuffer.append(" chisquare statistic = ");
            msgBuffer.append(chiSquareTest.chiSquare(expected, observed));
            msgBuffer.append(". \n");
            msgBuffer.append("value\texpected\tobserved\n");
            for (int i = 0; i < expected.length; i++) {
                msgBuffer.append(valueLabels[i]);
                msgBuffer.append("\t");

View Full Code Here

Examples of org.apache.commons.math3.stat.inference.ChiSquareTest

            expected[i] = (poissonDistribution.cumulativeProbability(binBounds.get(i) - 1) -
                poissonDistribution.cumulativeProbability(binBounds.get(i - 1) -1)) * sampleSize;
        }


        // Use chisquare test to verify that generated values are poisson(mean)-distributed
        ChiSquareTest chiSquareTest = new ChiSquareTest();
            // Fail if we can reject null hypothesis that distributions are the same
        if (chiSquareTest.chiSquareTest(expected, observed, alpha)) {
            StringBuilder msgBuffer = new StringBuilder();
            DecimalFormat df = new DecimalFormat("#.##");
            msgBuffer.append("Chisquare test failed for mean = ");
            msgBuffer.append(mean);
            msgBuffer.append(" p-value = ");
            msgBuffer.append(chiSquareTest.chiSquareTest(expected, observed));
            msgBuffer.append(" chisquare statistic = ");
            msgBuffer.append(chiSquareTest.chiSquare(expected, observed));
            msgBuffer.append(". \n");
            msgBuffer.append("bin\t\texpected\tobserved\n");
            for (int i = 0; i < expected.length; i++) {
                msgBuffer.append("[");
                msgBuffer.append(i == 0 ? 1: binBounds.get(i - 1));

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