Package org.apache.commons.math3.distribution

Examples of org.apache.commons.math3.distribution.ChiSquaredDistribution

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        TestUtils.assertChiSquareAccept(expected, counts, 0.001);
    }

    @Test
    public void testNextChiSquare() {
        double[] quartiles = TestUtils.getDistributionQuartiles(new ChiSquaredDistribution(12));
        long[] counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextChiSquare(12);
            TestUtils.updateCounts(value, counts, quartiles);
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     *
     * @param df the degrees of freedom of the ChiSquare distribution
     * @return random value sampled from the ChiSquare(df) distribution
     */
    public double nextChiSquare(double df) {
        return new ChiSquaredDistribution(getRandomGenerator(), df,
                ChiSquaredDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY).sample();
    }
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     */
    public double chiSquareTest(final double[] expected, final long[] observed)
        throws NotPositiveException, NotStrictlyPositiveException,
        DimensionMismatchException, MaxCountExceededException {

        ChiSquaredDistribution distribution =
            new ChiSquaredDistribution(expected.length - 1.0);
        return 1.0 - distribution.cumulativeProbability(chiSquare(expected, observed));
    }
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        throws NullArgumentException, DimensionMismatchException,
        NotPositiveException, MaxCountExceededException {

        checkArray(counts);
        double df = ((double) counts.length -1) * ((double) counts[0].length - 1);
        ChiSquaredDistribution distribution;
        distribution = new ChiSquaredDistribution(df);
        return 1 - distribution.cumulativeProbability(chiSquare(counts));

    }
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     */
    public double chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)
        throws DimensionMismatchException, NotPositiveException, ZeroException,
        MaxCountExceededException {

        ChiSquaredDistribution distribution;
        distribution = new ChiSquaredDistribution((double) observed1.length - 1);
        return 1 - distribution.cumulativeProbability(
                chiSquareDataSetsComparison(observed1, observed2));

    }
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     *
     * @param df the degrees of freedom of the ChiSquare distribution
     * @return random value sampled from the ChiSquare(df) distribution
     */
    public double nextChiSquare(double df) {
        return new ChiSquaredDistribution(getRan(), df,
                ChiSquaredDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY).sample();
    }
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     */
    public double gTest(final double[] expected, final long[] observed)
            throws NotPositiveException, NotStrictlyPositiveException,
            DimensionMismatchException, MaxCountExceededException {

        final ChiSquaredDistribution distribution =
                new ChiSquaredDistribution(expected.length - 1.0);
        return 1.0 - distribution.cumulativeProbability(
                g(expected, observed));
    }
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     */
    public double gTestIntrinsic(final double[] expected, final long[] observed)
            throws NotPositiveException, NotStrictlyPositiveException,
            DimensionMismatchException, MaxCountExceededException {

        final ChiSquaredDistribution distribution =
                new ChiSquaredDistribution(expected.length - 2.0);
        return 1.0 - distribution.cumulativeProbability(
                g(expected, observed));
    }
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     */
    public double gTestDataSetsComparison(final long[] observed1,
            final long[] observed2)
            throws DimensionMismatchException, NotPositiveException, ZeroException,
            MaxCountExceededException {
        final ChiSquaredDistribution distribution = new ChiSquaredDistribution(
                (double) observed1.length - 1);
        return 1 - distribution.cumulativeProbability(
                gDataSetsComparison(observed1, observed2));
    }
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        TestUtils.assertChiSquareAccept(expected, counts, 0.001);
    }

    @Test
    public void testNextChiSquare() {
        double[] quartiles = TestUtils.getDistributionQuartiles(new ChiSquaredDistribution(12));
        long[] counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextChiSquare(12);
            TestUtils.updateCounts(value, counts, quartiles);
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Related Classes of org.apache.commons.math3.distribution.ChiSquaredDistribution

  • org.apache.commons.math3.analysis.differentiation.DerivativeStructure
  • org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction
  • org.apache.commons.math3.analysis.function.HarmonicOscillator
  • org.apache.commons.math3.analysis.function.Sin
  • org.apache.commons.math3.analysis.function.Sinc
  • org.apache.commons.math3.analysis.MultivariateFunction
  • org.apache.commons.math3.analysis.QuinticFunction
  • org.apache.commons.math3.analysis.solvers.BrentSolver
  • org.apache.commons.math3.analysis.UnivariateFunction
  • org.apache.commons.math3.complex.Complex
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