Example usage for org.apache.commons.math3.exception.util LocalizedFormats SHAPE

Introduction

In this page you can find the example usage for org.apache.commons.math3.exception.util LocalizedFormats SHAPE.

Prototype

LocalizedFormats SHAPE

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Usage

From source file:gmc_hdfs.distribution.ParetoDistribution.java

/**
 * Creates a Pareto distribution.//w w w. j a va2 s.  co m
 *
 * @param rng Random number generator.
 * @param scale Scale parameter of this distribution.
 * @param shape Shape parameter of this distribution.
 * @param inverseCumAccuracy Inverse cumulative probability accuracy.
 * @throws NotStrictlyPositiveException if {@code scale <= 0} or {@code shape <= 0}.
 */
public ParetoDistribution(RandomGenerator rng, double scale, double shape, double inverseCumAccuracy)
        throws NotStrictlyPositiveException {
    super(rng);

    if (scale <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.SCALE, scale);
    }

    if (shape <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.SHAPE, shape);
    }

    this.scale = scale;
    this.shape = shape;
    this.solverAbsoluteAccuracy = inverseCumAccuracy;
}

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From source file:statalign.utils.GammaDistribution.java

/**
 * Creates a Gamma distribution.//from ww w.  j a  v  a 2 s.  co m
 *
 * @param rng Random number generator.
 * @param shape the shape parameter
 * @param scale the scale parameter
 * @param inverseCumAccuracy the maximum absolute error in inverse
 * cumulative probability estimates (defaults to
 * {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
 * @throws NotStrictlyPositiveException if {@code shape <= 0} or
 * {@code scale <= 0}.
 * @since 3.1
 */
public GammaDistribution(RandomGenerator rng, double shape, double scale, double inverseCumAccuracy)
        throws NotStrictlyPositiveException {
    super(rng);

    if (shape <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.SHAPE, shape);
    }
    if (scale <= 0) {
        throw new NotStrictlyPositiveException(LocalizedFormats.SCALE, scale);
    }

    this.shape = shape;
    this.scale = scale;
    this.solverAbsoluteAccuracy = inverseCumAccuracy;
    this.shiftedShape = shape + Gamma.LANCZOS_G + 0.5;
    final double aux = FastMath.E / (2.0 * FastMath.PI * shiftedShape);
    this.densityPrefactor2 = shape * FastMath.sqrt(aux) / Gamma.lanczos(shape);
    this.densityPrefactor1 = this.densityPrefactor2 / scale * FastMath.pow(shiftedShape, -shape)
            * FastMath.exp(shape + Gamma.LANCZOS_G);
    this.minY = shape + Gamma.LANCZOS_G - FastMath.log(Double.MAX_VALUE);
    this.maxLogY = FastMath.log(Double.MAX_VALUE) / (shape - 1.0);
}

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