com.opengamma.analytics.math.statistics.distribution.GeneralizedExtremeValueDistribution.java Source code

Introduction

Here is the source code for com.opengamma.analytics.math.statistics.distribution.GeneralizedExtremeValueDistribution.java

Source

/**
 * Copyright (C) 2009 - present by OpenGamma Inc. and the OpenGamma group of companies
 * 
 * Please see distribution for license.
 */
package com.opengamma.analytics.math.statistics.distribution;

import org.apache.commons.lang.NotImplementedException;
import org.apache.commons.lang.Validate;

import com.opengamma.util.CompareUtils;

/**
 * 
 * The generalized extreme value distribution is a family of continuous probability distributions that combines the Gumbel (type I),
 * Fréchet (type II) and Weibull (type III) families of distributions.
 * <p>
 * This distribution has location parameter $\mu$, shape parameter $\xi$
 * and scale parameter $\sigma$, with
 * $$
 * \begin{align*}
 * \mu&\in\Re,\\
 * \xi&\in\Re,\\
 * \sigma&>0
 * \end{align*}
 * $$
 * and support
 * $$
 * \begin{align*}
 * x\in
 * \begin{cases}
 * \left[\mu - \frac{\sigma}{\xi}, +\infty\right) & \text{when } \xi > 0\\
 * (-\infty,+\infty) & \text{when } \xi = 0\\\\
 * \left(-\infty, \mu - \frac{\sigma}{\xi}\right] & \text{when } \xi < 0
 * \end{cases}
 * \end{align*}
 * $$
 * The cdf is given by:
 * $$
 * \begin{align*}
 * F(x) &=e^{-t(x)}\\
 * t(x)&=
 * \begin{cases}
 * \left(1 + \xi\frac{x-\mu}{\sigma}\right)^{-\frac{1}{\xi}} & \text{if } \xi \neq 0,\\
 * e^{-\frac{x-\mu}{\sigma}} & \text{if } \xi = 0.
 * \end{cases}
 * \end{align*}
 * $$
 * and the pdf by:
 * $$
 * \begin{align*}
 * f(x)&=\frac{t(x)^{\xi + 1}e^{-t(x)}}{\sigma}\quad\\
 * t(x)&=
 * \begin{cases}
 * \left(1 + \xi\frac{x-\mu}{\sigma}\right)^{-\frac{1}{\xi}} & \text{if } \xi \neq 0,\\
 * e^{-\frac{x-\mu}{\sigma}} & \text{if } \xi = 0.
 * \end{cases}
 * \end{align*}
 * $$
 * 
 */
public class GeneralizedExtremeValueDistribution implements ProbabilityDistribution<Double> {
    private final double _mu;
    private final double _sigma;
    private final double _ksi;
    private final boolean _ksiIsZero;

    /**
     * 
     * @param mu The location parameter
     * @param sigma The scale parameter, not negative or zero
     * @param ksi The shape parameter
     */
    public GeneralizedExtremeValueDistribution(final double mu, final double sigma, final double ksi) {
        Validate.isTrue(sigma >= 0, "sigma must be >= 0");
        _mu = mu;
        _sigma = sigma;
        _ksi = ksi;
        _ksiIsZero = CompareUtils.closeEquals(ksi, 0, 1e-13);
    }

    /**
     * {@inheritDoc}
     * @throws IllegalArgumentException If $x \not\in$ support
     */
    @Override
    public double getCDF(final Double x) {
        Validate.notNull(x);
        return Math.exp(-getT(x));
    }

    /**
     * {@inheritDoc}
     * @return Not supported
     * @throws NotImplementedException
     */
    @Override
    public double getInverseCDF(final Double p) {
        throw new NotImplementedException();
    }

    /**
     * {@inheritDoc}
     * @throws IllegalArgumentException If $x \not\in$ support
     */
    @Override
    public double getPDF(final Double x) {
        Validate.notNull(x);
        final double t = getT(x);
        return Math.pow(t, _ksi + 1) * Math.exp(-t) / _sigma;
    }

    /**
     * {@inheritDoc}
     * @return Not supported
     * @throws NotImplementedException
     */
    @Override
    public double nextRandom() {
        throw new NotImplementedException();
    }

    /**
     * @return The location parameter
     */
    public double getMu() {
        return _mu;
    }

    /**
     * @return The scale parameter
     */
    public double getSigma() {
        return _sigma;
    }

    /**
     * @return The shape parameter
     */
    public double getKsi() {
        return _ksi;
    }

    private double getT(final double x) {
        if (_ksiIsZero) {
            return Math.exp(-(x - _mu) / _sigma);
        }
        if (_ksi < 0 && x > _mu - _sigma / _ksi) {
            throw new IllegalArgumentException(
                    "Support for GEV is in the range -infinity -> mu - sigma / ksi when ksi < 0");
        }
        if (_ksi > 0 && x < _mu - _sigma / _ksi) {
            throw new IllegalArgumentException(
                    "Support for GEV is in the range mu - sigma / ksi -> +infinity when ksi > 0");
        }
        return Math.pow(1 + _ksi * (x - _mu) / _sigma, -1. / _ksi);
    }

    @Override
    public int hashCode() {
        final int prime = 31;
        int result = 1;
        long temp;
        temp = Double.doubleToLongBits(_ksi);
        result = prime * result + (int) (temp ^ (temp >>> 32));
        temp = Double.doubleToLongBits(_mu);
        result = prime * result + (int) (temp ^ (temp >>> 32));
        temp = Double.doubleToLongBits(_sigma);
        result = prime * result + (int) (temp ^ (temp >>> 32));
        return result;
    }

    @Override
    public boolean equals(final Object obj) {
        if (this == obj) {
            return true;
        }
        if (obj == null) {
            return false;
        }
        if (getClass() != obj.getClass()) {
            return false;
        }
        final GeneralizedExtremeValueDistribution other = (GeneralizedExtremeValueDistribution) obj;
        if (Double.doubleToLongBits(_ksi) != Double.doubleToLongBits(other._ksi)) {
            return false;
        }
        if (Double.doubleToLongBits(_mu) != Double.doubleToLongBits(other._mu)) {
            return false;
        }
        return Double.doubleToLongBits(_sigma) == Double.doubleToLongBits(other._sigma);
    }

}