Package org.apache.commons.math3.distribution

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

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            container.add(comp, c);

            c.gridx++;
            comp = createComponent("Student-T", -5, 5,
                                   new String[] { "df=1", "df=2", "df=5", "df=10000" },
                                   new TDistribution(1),
                                   new TDistribution(2),
                                   new TDistribution(5),
                                   new TDistribution(10000));                              
            container.add(comp, c);

            c.gridx++;
            comp = createComponent("Weibull", 0, 3,
                                   new String[] { "λ=0.5,k=1", "λ=1,k=1", "λ=1.5,k=1", "λ=5,k=1" },
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     * @throws org.apache.commons.math3.exception.MaxCountExceededException
     * if an error occurs estimating probabilities
     * @throws NullPointerException if this instance was created with no data
     */
    public RealMatrix getCorrelationPValues() {
        TDistribution tDistribution = new TDistribution(nObs - 2);
        int nVars = correlationMatrix.getColumnDimension();
        double[][] out = new double[nVars][nVars];
        for (int i = 0; i < nVars; i++) {
            for (int j = 0; j < nVars; j++) {
                if (i == j) {
                    out[i][j] = 0d;
                } else {
                    double r = correlationMatrix.getEntry(i, j);
                    double t = FastMath.abs(r * FastMath.sqrt((nObs - 2)/(1 - r * r)));
                    out[i][j] = 2 * tDistribution.cumulativeProbability(-t);
                }
            }
        }
        return new BlockRealMatrix(out);
    }
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        if (alpha >= 1 || alpha <= 0) {
            throw new OutOfRangeException(LocalizedFormats.SIGNIFICANCE_LEVEL,
                                          alpha, 0, 1);
        }
        // No advertised NotStrictlyPositiveException here - will return NaN above
        TDistribution distribution = new TDistribution(n - 2);
        return getSlopeStdErr() *
            distribution.inverseCumulativeProbability(1d - alpha / 2d);
    }
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    public double getSignificance() {
        if (n < 3) {
            return Double.NaN;
        }
        // No advertised NotStrictlyPositiveException here - will return NaN above
        TDistribution distribution = new TDistribution(n - 2);
        return 2d * (1.0 - distribution.cumulativeProbability(
                    FastMath.abs(getSlope()) / getSlopeStdErr()));
    }
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        TestUtils.assertChiSquareAccept(expected, counts, 0.001);
    }

    @Test
    public void testNextT() {
        double[] quartiles = TestUtils.getDistributionQuartiles(new TDistribution(10));
        long[] counts = new long[4];
        randomData.reSeed(1000);
        for (int i = 0; i < 1000; i++) {
            double value = randomData.nextT(10);
            TestUtils.updateCounts(value, counts, quartiles);
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     * @param df the degrees of freedom of the T distribution
     * @return random value from the T(df) distribution
     * @throws NotStrictlyPositiveException if {@code df <= 0}
     */
    public double nextT(double df) throws NotStrictlyPositiveException {
        return new TDistribution(getRandomGenerator(), df,
                TDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY).sample();
    }
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    protected double tTest(final double m, final double mu,
                           final double v, final double n)
        throws MaxCountExceededException, MathIllegalArgumentException {

        double t = FastMath.abs(t(m, mu, v, n));
        TDistribution distribution = new TDistribution(n - 1);
        return 2.0 * distribution.cumulativeProbability(-t);

    }
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                           final double n1, final double n2)
        throws MaxCountExceededException, NotStrictlyPositiveException {

        final double t = FastMath.abs(t(m1, m2, v1, v2, n1, n2));
        final double degreesOfFreedom = df(v1, v2, n1, n2);
        TDistribution distribution = new TDistribution(degreesOfFreedom);
        return 2.0 * distribution.cumulativeProbability(-t);

    }
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                                        double n1, double n2)
        throws MaxCountExceededException, NotStrictlyPositiveException {

        final double t = FastMath.abs(homoscedasticT(m1, m2, v1, v2, n1, n2));
        final double degreesOfFreedom = n1 + n2 - 2;
        TDistribution distribution = new TDistribution(degreesOfFreedom);
        return 2.0 * distribution.cumulativeProbability(-t);

    }
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     * @return matrix of p-values
     * @throws org.apache.commons.math3.exception.MaxCountExceededException
     * if an error occurs estimating probabilities
     */
    public RealMatrix getCorrelationPValues() {
        TDistribution tDistribution = new TDistribution(nObs - 2);
        int nVars = correlationMatrix.getColumnDimension();
        double[][] out = new double[nVars][nVars];
        for (int i = 0; i < nVars; i++) {
            for (int j = 0; j < nVars; j++) {
                if (i == j) {
                    out[i][j] = 0d;
                } else {
                    double r = correlationMatrix.getEntry(i, j);
                    double t = FastMath.abs(r * FastMath.sqrt((nObs - 2)/(1 - r * r)));
                    out[i][j] = 2 * tDistribution.cumulativeProbability(-t);
                }
            }
        }
        return new BlockRealMatrix(out);
    }
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Related Classes of org.apache.commons.math3.distribution.TDistribution

  • 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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