All Downloads are FREE. Search and download functionalities are using the official Maven repository.

org.apache.commons.numbers.gamma.Gamma Maven / Gradle / Ivy

Go to download

Statistical sampling library for use in virtdata libraries, based on apache commons math 4

There is a newer version: 5.17.0
Show newest version
/*
 * 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.numbers.gamma;


/**
 * Gamma
 * function.
 * 

* The gamma * function can be seen to extend the factorial function to cover real and * complex numbers, but with its argument shifted by {@code -1}. This * implementation supports real numbers. *

*

* This class is immutable. *

*/ public class Gamma { /** √(2π). */ private static final double SQRT_TWO_PI = 2.506628274631000502; /** * Computes the value of \( \Gamma(x) \). *

* Based on the NSWC Library of Mathematics Subroutines double * precision implementation, {@code DGAMMA}. * * @param x Argument. * @return \( \Gamma(x) \) */ public static double value(final double x) { if ((x == Math.rint(x)) && (x <= 0.0)) { return Double.NaN; } final double absX = Math.abs(x); if (absX <= 20) { if (x >= 1) { /* * From the recurrence relation * Gamma(x) = (x - 1) * ... * (x - n) * Gamma(x - n), * then * Gamma(t) = 1 / [1 + InvGamma1pm1.value(t - 1)], * where t = x - n. This means that t must satisfy * -0.5 <= t - 1 <= 1.5. */ double prod = 1; double t = x; while (t > 2.5) { t -= 1; prod *= t; } return prod / (1 + InvGamma1pm1.value(t - 1)); } else { /* * From the recurrence relation * Gamma(x) = Gamma(x + n + 1) / [x * (x + 1) * ... * (x + n)] * then * Gamma(x + n + 1) = 1 / [1 + InvGamma1pm1.value(x + n)], * which requires -0.5 <= x + n <= 1.5. */ double prod = x; double t = x; while (t < -0.5) { t += 1; prod *= t; } return 1 / (prod * (1 + InvGamma1pm1.value(t))); } } else { final double y = absX + LanczosApproximation.g() + 0.5; final double gammaAbs = SQRT_TWO_PI / absX * Math.pow(y, absX + 0.5) * Math.exp(-y) * LanczosApproximation.value(absX); if (x > 0) { return gammaAbs; } else { /* * From the reflection formula * Gamma(x) * Gamma(1 - x) * sin(pi * x) = pi, * and the recurrence relation * Gamma(1 - x) = -x * Gamma(-x), * it is found * Gamma(x) = -pi / [x * sin(pi * x) * Gamma(-x)]. */ return -Math.PI / (x * Math.sin(Math.PI * x) * gammaAbs); } } } }





© 2015 - 2024 Weber Informatics LLC | Privacy Policy