Example usage for org.apache.commons.math.special Beta regularizedBeta

Introduction

In this page you can find the example usage for org.apache.commons.math.special Beta regularizedBeta.

Prototype

public static double regularizedBeta(double x, double a, double b) throws MathException 

Source Link

Document

Returns the <a href="http://mathworld.wolfram.com/RegularizedBetaFunction.html"> regularized beta function</a> I(x, a, b).

Usage

From source file:dr.math.distributions.NegativeBinomialDistribution.java

public double quantile(double y) {
    // TB - I'm having trouble implementing this
    // LM - A first stab using simple minimisation to invert the function (under absolute loss)
    // Implementation based on the qnbinom.c function used in R
    final double stdev = Math.sqrt(mean + (mean * mean * alpha));
    final double r = -1 * (mean * mean) / (mean - stdev * stdev);
    final double p = mean / (stdev * stdev);
    final double prob = y;

    final double Q = 1.0 / p;
    final double P = (1.0 - p) * Q;
    final double gamma = (Q + P) / stdev;
    final double z = Math.sqrt(2.0) * ErrorFunction.inverseErf(2.0 * y - 1.0);
    final double crudeY = mean + stdev * (z + gamma * (z * z - 1) / 6);

    UnivariateFunction f = new UnivariateFunction() {
        double tent = Double.NaN;

        public double evaluate(final double argument) {
            try {
                tent = Beta.regularizedBeta(p, r, argument + 1);
            } catch (MathException e) {
                return Double.NaN;
            }/*from w ww  .j  av  a 2  s .  c om*/
            double score = Math.abs(tent - prob);
            return score;
        }

        public int getNumArguments() {
            return 1;
        }

        public double getLowerBound() { // 20% window should cut it. Probably too large even...
            return Math.min(crudeY - .2 * crudeY, 0);
        }

        public double getUpperBound() {
            return crudeY + .2 * crudeY;
        }
    };
    UnivariateMinimum minimum = new UnivariateMinimum();
    double q = minimum.findMinimum(f);
    return Math.ceil(q);
}

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From source file:geogebra.util.MyMath.java

final public static double betaIncomplete(double a, double b, double x) {

    try {/*from ww  w. j  a va 2s.  co  m*/
        return Beta.regularizedBeta(x, a, b) * beta(a, b);
    } catch (MathException e) {
        return Double.NaN;
    }

}

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From source file:geogebra.util.MyMath.java

final public static double betaIncompleteRegularized(double a, double b, double x) {

    try {/*from w ww  .j av  a  2s.c o  m*/
        return Beta.regularizedBeta(x, a, b);
    } catch (MathException e) {
        return Double.NaN;
    }
}

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From source file:dr.math.distributions.NegativeBinomialDistribution.java

public static double cdf(double x, double mean, double alpha) {
    double theta = 1.0 / alpha;
    double p = theta / (theta + mean);
    try {/*from   w w  w . j a  va  2  s.co  m*/
        return Beta.regularizedBeta(p, theta, x + 1);
    } catch (MathException e) {
        // AR - throwing exceptions deep in numerical code causes trouble. Catching runtime
        // exceptions is bad. Better to return NaN and let the calling code deal with it.
        return Double.NaN;
        //                throw MathRuntimeException.createIllegalArgumentException(
        //                "Couldn't calculate beta cdf for alpha = " + alpha + ", beta = " + beta + ": " +e.getMessage());
    }
}

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From source file:dr.math.distributions.BetaDistribution.java

public double cdf(double x) {
    if (x <= 0) {
        return 0;
    } else if (x >= 1) {
        return 1;
    } else {// www .  j  a  va2s.co m
        try {
            return Beta.regularizedBeta(x, alpha, beta);
        } catch (MathException e) {
            // AR - throwing exceptions deep in numerical code causes trouble. Catching runtime
            // exceptions is bad. Better to return NaN and let the calling code deal with it.
            return Double.NaN;
            //                throw MathRuntimeException.createIllegalArgumentException(
            //                "Couldn't calculate beta cdf for alpha = " + alpha + ", beta = " + beta + ": " +e.getMessage());
        }
    }

}

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From source file:dr.math.distributions.BetaDistribution.java

public double cumulativeProbability(double x) throws MathException {
    if (x <= 0) {
        return 0;
    } else if (x >= 1) {
        return 1;
    } else {//www  . ja  v  a 2  s.c om
        return Beta.regularizedBeta(x, alpha, beta);
    }
}

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