com.github.tommyettinger.random.distribution.BetaPrimeDistribution Maven / Gradle / Ivy
/*
* Copyright (c) 2023 See AUTHORS file.
*
* Licensed 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 com.github.tommyettinger.random.distribution;
import com.github.tommyettinger.digital.MathTools;
import com.github.tommyettinger.random.EnhancedRandom;
import com.github.tommyettinger.random.AceRandom;
/**
* A two-parameter distribution with range from 0 to positive infinity.
* @see Wikipedia's page on this distribution.
*/
public class BetaPrimeDistribution extends Distribution {
public String getTag() {
return "BetaPrime";
}
@Override
public BetaPrimeDistribution copy() {
return new BetaPrimeDistribution(generator.copy(), alpha, beta);
}
private double alpha;
private double beta;
public double getAlpha() {
return alpha;
}
public double getBeta() {
return beta;
}
@Override
public double getParameterA() {
return alpha;
}
@Override
public double getParameterB() {
return beta;
}
/**
* Uses an {@link AceRandom}, alpha = 2.0, beta = 2.0 .
*/
public BetaPrimeDistribution() {
this(new AceRandom(), 2.0, 2.0);
}
/**
* Uses an {@link AceRandom} and the given alpha and beta.
*/
public BetaPrimeDistribution(double alpha, double beta) {
this(new AceRandom(), alpha, beta);
}
/**
* Uses the given EnhancedRandom directly. Uses the given alpha and beta.
*/
public BetaPrimeDistribution(EnhancedRandom generator, double alpha, double beta)
{
this.generator = generator;
if(!setParameters(alpha, beta, 0.0))
throw new IllegalArgumentException("Given alpha and/or beta are invalid.");
}
@Override
public double getMaximum() {
return Double.POSITIVE_INFINITY;
}
@Override
public double getMean() {
return alpha / (beta - 1.0);
}
@Override
public double getMedian() {
throw new UnsupportedOperationException("Median is undefined.");
}
@Override
public double getMinimum() {
return 0.0;
}
@Override
public double[] getMode() {
return new double[]{(alpha - 1.0) / (beta + 1.0)};
}
@Override
public double getVariance() {
if(beta > 2.0)
return alpha * (alpha + beta - 1.0) / MathTools.square(beta - 1.0) * (beta - 2.0);
throw new UnsupportedOperationException("Variance cannot be determined for the given parameters.");
}
/**
* Sets all parameters and returns true if they are valid, otherwise leaves parameters unchanged and returns false.
* @param a alpha; should be greater than 1.0
* @param b beta; should be greater than 1.0
* @param c ignored
* @return true if the parameters given are valid and will be used
*/
@Override
public boolean setParameters(double a, double b, double c) {
if(a > 1.0 && b > 1.0){
alpha = a;
beta = b;
return true;
}
return false;
}
@Override
public double nextDouble() {
return sample(generator, alpha, beta);
}
public static double sample(EnhancedRandom generator, double alpha, double beta) {
double variate = BetaDistribution.sample(generator, alpha, beta);
double rev = 1.0 - variate;
return MathTools.isZero(rev, 0x1p-66) ? Double.POSITIVE_INFINITY : variate / rev;
}
}
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