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Statistical sampling library for use in virtdata libraries, based
on apache commons math 4
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.commons.statistics.distribution;
/**
* This class implements the Gumbel distribution.
*/
public class GumbelDistribution extends AbstractContinuousDistribution {
/** π2/6. */
private static final double PI_SQUARED_OVER_SIX = Math.PI * Math.PI / 6;
/**
*
* Approximation of Euler's constant.
*/
private static final double EULER = Math.PI / (2 * Math.E);
/** Location parameter. */
private final double mu;
/** Scale parameter. */
private final double beta;
/**
* Creates a distribution.
*
* @param mu location parameter
* @param beta scale parameter (must be positive)
* @throws IllegalArgumentException if {@code beta <= 0}
*/
public GumbelDistribution(double mu,
double beta) {
if (beta <= 0) {
throw new DistributionException(DistributionException.NEGATIVE, beta);
}
this.beta = beta;
this.mu = mu;
}
/**
* Gets the location parameter.
*
* @return the location parameter.
*/
public double getLocation() {
return mu;
}
/**
* Gets the scale parameter.
*
* @return the scale parameter.
*/
public double getScale() {
return beta;
}
/** {@inheritDoc} */
@Override
public double density(double x) {
final double z = (x - mu) / beta;
final double t = Math.exp(-z);
return Math.exp(-z - t) / beta;
}
/** {@inheritDoc} */
@Override
public double cumulativeProbability(double x) {
final double z = (x - mu) / beta;
return Math.exp(-Math.exp(-z));
}
/** {@inheritDoc} */
@Override
public double inverseCumulativeProbability(double p) {
if (p < 0 || p > 1) {
throw new DistributionException(DistributionException.OUT_OF_RANGE, p, 0, 1);
} else if (p == 0) {
return Double.NEGATIVE_INFINITY;
} else if (p == 1) {
return Double.POSITIVE_INFINITY;
}
return mu - Math.log(-Math.log(p)) * beta;
}
/** {@inheritDoc} */
@Override
public double getMean() {
return mu + EULER * beta;
}
/** {@inheritDoc} */
@Override
public double getVariance() {
return PI_SQUARED_OVER_SIX * beta * beta;
}
/** {@inheritDoc} */
@Override
public double getSupportLowerBound() {
return Double.NEGATIVE_INFINITY;
}
/** {@inheritDoc} */
@Override
public double getSupportUpperBound() {
return Double.POSITIVE_INFINITY;
}
/** {@inheritDoc} */
@Override
public boolean isSupportConnected() {
return true;
}
}