Examples of cumulativeProbability()

@param x the value at which the CDF is evaluated. @return CDF for this distribution. @throws MathException if the cumulative probability can not becomputed due to convergence or other numerical errors.
  • org.apache.commons.math.distribution.NormalDistributionImpl.cumulativeProbability()
    For this distribution, X, this method returns P(X < x). If xis more than 40 standard deviations from the mean, 0 or 1 is returned, as in these cases the actual value is within Double.MIN_VALUE of 0 or 1. @param x the value at which the CDF is evaluated. @return CDF evaluated at x. @throws MathException if the algorithm fails to converge
  • org.apache.commons.math.distribution.PoissonDistribution.cumulativeProbability()
  • org.apache.commons.math.distribution.PoissonDistributionImpl.cumulativeProbability()
    The probability distribution function P(X <= x) for a Poisson distribution. @param x the value at which the PDF is evaluated. @return Poisson distribution function evaluated at x @throws MathException if the cumulative probability can not be computeddue to convergence or other numerical errors.
  • org.apache.commons.math.distribution.TDistribution.cumulativeProbability()
  • org.apache.commons.math.distribution.TDistributionImpl.cumulativeProbability()
    For this distribution, X, this method returns P(X < x). @param x the value at which the CDF is evaluated. @return CDF evaluated at x. @throws MathException if the cumulative probability can not becomputed due to convergence or other numerical errors.
  • org.apache.commons.math.distribution.WeibullDistribution.cumulativeProbability()
  • org.apache.commons.math3.distribution.BetaDistribution.cumulativeProbability()
    {@inheritDoc}
  • org.apache.commons.math3.distribution.BinomialDistribution.cumulativeProbability()
    {@inheritDoc}
  • org.apache.commons.math3.distribution.ChiSquaredDistribution.cumulativeProbability()
    {@inheritDoc}
  • org.apache.commons.math3.distribution.FDistribution.cumulativeProbability()
    orld.wolfram.com/F-Distribution.html"> F-Distribution, equation (4).
  • org.apache.commons.math3.distribution.GammaDistribution.cumulativeProbability()
    orld.wolfram.com/Chi-SquaredDistribution.html"> Chi-Squared Distribution, equation (9).
  • Casella, G., & Berger, R. (1990). Statistical Inference. Belmont, CA: Duxbury Press.
  • org.apache.commons.math3.distribution.IntegerDistribution.cumulativeProbability()
    For a random variable {@code X} whose values are distributed accordingto this distribution, this method returns {@code P(X <= x)}. In other words, this method represents the (cumulative) distribution function (CDF) for this distribution. @param x the point at which the CDF is evaluated @return the probability that a random variable with thisdistribution takes a value less than or equal to {@code x}
  • org.apache.commons.math3.distribution.NormalDistribution.cumulativeProbability()
    {@inheritDoc}If {@code x} is more than 40 standard deviations from the mean, 0 or 1is returned, as in these cases the actual value is within {@code Double.MIN_VALUE} of 0 or 1.
  • org.apache.commons.math3.distribution.PoissonDistribution.cumulativeProbability()
    {@inheritDoc}
  • org.apache.commons.math3.distribution.RealDistribution.cumulativeProbability()
    For a random variable {@code X} whose values are distributed accordingto this distribution, this method returns {@code P(x0 < X <= x1)}. @param x0 the exclusive lower bound @param x1 the inclusive upper bound @return the probability that a random variable with this distributiontakes a value between {@code x0} and {@code x1}, excluding the lower and including the upper endpoint @throws NumberIsTooLargeException if {@code x0> x1} @deprecated As of 3.1. In 4.0, this method will be renamed{@code probability(double x0, double x1)}.
  • org.apache.commons.math3.distribution.TDistribution.cumulativeProbability()
    {@inheritDoc}

    • Examples of org.apache.commons.math3.distribution.ChiSquaredDistribution.cumulativeProbability()

    153
    154
    155
    156
    157
    158
    159
    160
    161
    162
    163
                DimensionMismatchException, MaxCountExceededException {

            // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
            final ChiSquaredDistribution distribution =
                    new ChiSquaredDistribution(null, expected.length - 1.0);
            return 1.0 - distribution.cumulativeProbability(g(expected, observed));
        }

        /**
         * Returns the intrinsic (Hardy-Weinberg proportions) p-Value, as described
         * in p64-69 of McDonald, J.H. 2009. Handbook of Biological Statistics
    View Full Code Here

    Examples of org.apache.commons.math3.distribution.ChiSquaredDistribution.cumulativeProbability()

    184
    185
    186
    187
    188
    189
    190
    191
    192
    193
    194
                DimensionMismatchException, MaxCountExceededException {

            // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
            final ChiSquaredDistribution distribution =
                    new ChiSquaredDistribution(null, expected.length - 2.0);
            return 1.0 - distribution.cumulativeProbability(g(expected, observed));
        }

        /**
         * Performs a G-Test (Log-Likelihood Ratio Test) for goodness of fit
         * evaluating the null hypothesis that the observed counts conform to the
    View Full Code Here

    Examples of org.apache.commons.math3.distribution.ChiSquaredDistribution.cumulativeProbability()

    474
    475
    476
    477
    478
    479
    480
    481
    482
    483
    484
                MaxCountExceededException {

            // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
            final ChiSquaredDistribution distribution =
                    new ChiSquaredDistribution(null, (double) observed1.length - 1);
            return 1 - distribution.cumulativeProbability(
                    gDataSetsComparison(observed1, observed2));
        }

        /**
         * <p>Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned
    View Full Code Here

    Examples of org.apache.commons.math3.distribution.ChiSquaredDistribution.cumulativeProbability()

    155
    156
    157
    158
    159
    160
    161
    162
    163
    164
    165
            throws NotPositiveException, NotStrictlyPositiveException,
            DimensionMismatchException, MaxCountExceededException {

            ChiSquaredDistribution distribution =
                new ChiSquaredDistribution(expected.length - 1.0);
            return 1.0 - distribution.cumulativeProbability(chiSquare(expected, observed));

        }

        /**
         * Performs a <a href="http://www.itl.nist.gov/div898/handbook/eda/section3/eda35f.htm">
    View Full Code Here

    Examples of org.apache.commons.math3.distribution.ChiSquaredDistribution.cumulativeProbability()

    313
    314
    315
    316
    317
    318
    319
    320
    321
    322
    323
            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));

        }

        /**
         * Performs a <a href="http://www.itl.nist.gov/div898/handbook/prc/section4/prc45.htm">
    View Full Code Here

    Examples of org.apache.commons.math3.distribution.ChiSquaredDistribution.cumulativeProbability()

    509
    510
    511
    512
    513
    514
    515
    516
    517
    518
    519
            throws DimensionMismatchException, NotPositiveException, ZeroException,
            MaxCountExceededException {

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

        }

        /**
     
    View Full Code Here

    Examples of org.apache.commons.math3.distribution.FDistribution.cumulativeProbability()

    126
    127
    128
    129
    130
    131
    132
    133
    134
    135
    136
            final AnovaStats a = anovaStats(categoryData);
            // No try-catch or advertised exception because args are valid
            // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
            final FDistribution fdist = new FDistribution(null, a.dfbg, a.dfwg);
            return 1.0 - fdist.cumulativeProbability(a.F);

        }

        /**
         * Computes the ANOVA P-value for a collection of {@link SummaryStatistics}.
    View Full Code Here

    Examples of org.apache.commons.math3.distribution.FDistribution.cumulativeProbability()

    168
    169
    170
    171
    172
    173
    174
    175
    176
    177
    178
                   ConvergenceException, MaxCountExceededException {

            final AnovaStats a = anovaStats(categoryData, allowOneElementData);
            // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
            final FDistribution fdist = new FDistribution(null, a.dfbg, a.dfwg);
            return 1.0 - fdist.cumulativeProbability(a.F);

        }

        /**
         * This method calls the method that actually does the calculations (except
    View Full Code Here

    Examples of org.apache.commons.math3.distribution.FDistribution.cumulativeProbability()

    124
    125
    126
    127
    128
    129
    130
    131
    132
    133
    134
            throws NullArgumentException, DimensionMismatchException,
            ConvergenceException, MaxCountExceededException {

            AnovaStats a = anovaStats(categoryData);
            FDistribution fdist = new FDistribution(a.dfbg, a.dfwg);
            return 1.0 - fdist.cumulativeProbability(a.F);

        }

        /**
         * Performs an ANOVA test, evaluating the null hypothesis that there
    View Full Code Here

    Examples of org.apache.commons.math3.distribution.GammaDistribution.cumulativeProbability()

    64
    65
    66
    67
    68
    69
    70
    71
    72
    73
    74
            TDistribution tDistribution = new TDistribution(2);
            for (double q : new double[]{0.001, 0.01, 0.1, 0.2, 0.5, 0.8, 0.9, 0.99, 0.99}) {
                double uG1 = gd1.cumulativeProbability(tdG1.quantile(q));
                assertEquals(q, uG1, (1 - q) * q * 10e-2);

                double uG2 = gd2.cumulativeProbability(tdG2.quantile(q));
                assertEquals(q, uG2, (1 - q) * q * 10e-2);

                double u1 = normalDistribution.cumulativeProbability(td1.quantile(q));
                assertEquals(q, u1, (1 - q) * q * 10e-2);

     
    View Full Code Here
    TOP
    Copyright © 2018 www.massapi.com. All rights reserved.
    All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.