Added Pascal distribution contributed in BZ #38766.
git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@381115 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz
parent
c8cd287a53
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# Copyright 2006 The Apache Software Foundation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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#------------------------------------------------------------------------------
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# R source file to validate Pascal distribution tests in
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# org.apache.commons.math.distribution.PascalDistributionTest
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#
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# To run the test, install R, put this file and testFunctions
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# into the same directory, launch R from this directory and then enter
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# source("<name-of-this-file>")
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#
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# R functions used
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# dnbinom(x, size, prob, mu, log = FALSE) <- density
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# pnbinom(q, size, prob, mu, lower.tail = TRUE, log.p = FALSE) <- distribution
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# qnbinom(p, size, prob, mu, lower.tail = TRUE, log.p = FALSE) <- quantiles
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#------------------------------------------------------------------------------
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tol <- 1E-4 # error tolerance for tests
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#------------------------------------------------------------------------------
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# Function definitions
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source("testFunctions") # utility test functions
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# function to verify density computations
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verifyDensity <- function(points, expected, size, p, tol) {
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rDensityValues <- rep(0, length(points))
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i <- 0
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for (point in points) {
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i <- i + 1
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rDensityValues[i] <- dnbinom(point, size, p)
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}
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output <- c("Density test size = ", size, ", p = ", p)
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if (assertEquals(expected,rDensityValues,tol,"Density Values")) {
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displayPadded(output, SUCCEEDED, WIDTH)
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} else {
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displayPadded(output, FAILED, WIDTH)
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}
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}
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# function to verify distribution computations
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verifyDistribution <- function(points, expected, size, p, tol) {
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rDistValues <- rep(0, length(points))
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i <- 0
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for (point in points) {
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i <- i + 1
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rDistValues[i] <- pnbinom(point, size, p)
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}
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output <- c("Distribution test size = ", size, ", p = ", p)
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if (assertEquals(expected,rDistValues,tol,"Distribution Values")) {
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displayPadded(output, SUCCEEDED, WIDTH)
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} else {
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displayPadded(output, FAILED, WIDTH)
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}
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}
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#--------------------------------------------------------------------------
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cat("Negative Binomial test cases\n")
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size <- 10.0
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probability <- 0.70
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densityPoints <- c(-1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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densityValues <- c(0, 0.02824, 0.08474, 0.13982,
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0.16779, 0.16359, 0.1374, 0.10306, 0.070673, 0.04505, 0.02703,
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0.01540, 0.0084)
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distributionValues <- c(0, 0.02824, 0.11299, 0.25281, 0.42060, 0.58420,
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0.72162, 0.82468, 0.89535, 0.94041, 0.967446, 0.98285, 0.99125)
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inverseCumPoints <- c( 0, 0.001, 0.010, 0.025, 0.050, 0.100, 0.999,
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0.990, 0.975, 0.950, 0.900)
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inverseCumValues <- c(-1, -1, -1, -1, 0, 0, 13, 10, 9, 8, 7)
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verifyDensity(densityPoints,densityValues,size,probability,tol)
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verifyDistribution(densityPoints, distributionValues, size, probability, tol)
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i <- 0
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rInverseCumValues <- rep(0,length(inverseCumPoints))
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for (point in inverseCumPoints) {
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i <- i + 1
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rInverseCumValues[i] <- qnbinom(point, size, probability)
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}
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output <- c("Inverse Distribution test n = ", size, ", p = ", probability)
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# R defines quantiles from the right, need to subtract one
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if (assertEquals(inverseCumValues, rInverseCumValues-1, tol,
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"Inverse Dist Values")) {
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displayPadded(output, SUCCEEDED, 80)
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} else {
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displayPadded(output, FAILED, 80)
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}
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# Degenerate cases
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size <- 5
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probability <- 0.0
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densityPoints <- c(-1, 0, 1, 10, 11)
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densityValues <- c(0, 0, 0, 0, 0)
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distributionPoints <- c(-1, 0, 1, 5, 10)
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distributionValues <- c(0, 0, 0, 0, 0)
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verifyDensity(densityPoints,densityValues,size,probability,tol)
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verifyDistribution(distributionPoints,distributionValues,size,probability,tol)
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size <- 5
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probability <- 1.0
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densityPoints <- c(-1, 0, 1, 2, 5, 10)
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densityValues <- c(0, 1, 0, 0, 1, 0)
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distributionPoints <- c(-1, 0, 1, 2, 5, 10)
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distributionValues <- c(0, 1, 1, 1, 1, 1)
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verifyDensity(densityPoints,densityValues,size,probability,tol)
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verifyDistribution(distributionPoints,distributionValues,size,probability,tol)
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displayDashes(WIDTH)
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@ -33,6 +33,7 @@ import org.apache.commons.discovery.tools.DiscoverClass;
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* <li>Normal</li>
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* <li>Student's t</li>
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* <li>Weibull</li>
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* <li>Pascal</li>
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* </ul>
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*
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* Common usage:<pre>
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@ -80,6 +81,17 @@ public abstract class DistributionFactory {
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public abstract BinomialDistribution createBinomialDistribution(
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int numberOfTrials, double probabilityOfSuccess);
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/**
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* Create a Pascal distribution with the given number of successes and
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* probability of success.
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*
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* @param numberOfSuccesses the number of successes.
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* @param probabilityOfSuccess the probability of success
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* @return a new Pascal distribution
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*/
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public abstract PascalDistribution createPascalDistribution(
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int numberOfSuccesses, double probabilityOfSuccess);
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/**
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* Create a new cauchy distribution with the given median and scale.
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* @param median the median of the distribution
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@ -154,4 +154,16 @@ public class DistributionFactoryImpl extends DistributionFactory {
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return new PoissonDistributionImpl(lambda);
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}
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/**
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* Create a Pascal distribution with the given number of successes and
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* probability of success.
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*
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* @param numberOfSuccesses the number of successes.
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* @param probabilityOfSuccess the probability of success
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* @return a new Pascal distribution
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*/
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public PascalDistribution createPascalDistribution(int numberOfSuccesses, double probabilityOfSuccess) {
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return new PascalDistributionImpl(numberOfSuccesses, probabilityOfSuccess);
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}
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}
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@ -0,0 +1,62 @@
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/*
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* Copyright 2006 The Apache Software Foundation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math.distribution;
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/**
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* The Pascal Distribution.
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*
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* Instances of PascalDistribution objects should be created using
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* {@link DistributionFactory#createPascalDistribution(int, double)}.
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*
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* <p>
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* References:
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* <ul>
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* <li><a href="http://mathworld.wolfram.com/NegativeBinomialDistribution.html">
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* Negative Binomial Distribution</a></li>
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* </ul>
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* </p>
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*
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* @version $Revision:$
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*/
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public interface PascalDistribution extends IntegerDistribution {
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/**
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* Access the number of successes for this distribution.
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*
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* @return the number of successes
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*/
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int getNumberOfSuccesses();
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/**
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* Access the probability of success for this distribution.
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*
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* @return the probability of success
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*/
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double getProbabilityOfSuccess();
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/**
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* Change the number of successes for this distribution.
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*
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* @param successes the new number of successes
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*/
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void setNumberOfSuccesses(int successes);
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/**
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* Change the probability of success for this distribution.
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*
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* @param p the new probability of success
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*/
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void setProbabilityOfSuccess(double p);
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}
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@ -0,0 +1,104 @@
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/*
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* Copyright 2006 The Apache Software Foundation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math.distribution;
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/**
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* Test cases for PascalDistribution.
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* Extends IntegerDistributionAbstractTest. See class javadoc for
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* IntegerDistributionAbstractTest for details.
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*
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* @version $Revision:$ $Date:$
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*/
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public class PascalDistributionTest extends IntegerDistributionAbstractTest {
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/**
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* Constructor for PascalDistributionTest.
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* @param name
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*/
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public PascalDistributionTest(String name) {
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super(name);
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}
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//-------------- Implementations for abstract methods -----------------------
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/** Creates the default discrete distribution instance to use in tests. */
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public IntegerDistribution makeDistribution() {
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return DistributionFactory.newInstance().createPascalDistribution(10,0.70);
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}
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/** Creates the default probability density test input values */
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public int[] makeDensityTestPoints() {
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return new int[] {-1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11};
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}
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/** Creates the default probability density test expected values */
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public double[] makeDensityTestValues() {
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return new double[] {0d, 0.02824d, 0.08474d, 0.13982d,
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0.16779d, 0.16359d, 0.1374d, 0.10306d, 0.070673d, 0.04505d, 0.02703d, 0.01540d, 0.0084};
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}
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/** Creates the default cumulative probability density test input values */
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public int[] makeCumulativeTestPoints() {
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return makeDensityTestPoints();
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}
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/** Creates the default cumulative probability density test expected values */
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public double[] makeCumulativeTestValues() {
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return new double[] {0d, 0.02824d, 0.11299d, 0.25281d, 0.42060d, 0.58420d,
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0.72162d, 0.82468d, 0.89535d, 0.94041d, 0.967446d, 0.98285, 0.99125d};
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}
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/** Creates the default inverse cumulative probability test input values */
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public double[] makeInverseCumulativeTestPoints() {
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return new double[] {0, 0.001d, 0.010d, 0.025d, 0.050d, 0.100d, 0.999d,
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0.990d, 0.975d, 0.950d, 0.900d, 1};
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}
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/** Creates the default inverse cumulative probability density test expected values */
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public int[] makeInverseCumulativeTestValues() {
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return new int[] {-1, -1, -1, -1, 0, 0, 13, 10, 9, 8, 7, Integer.MAX_VALUE};
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}
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//----------------- Additional test cases ---------------------------------
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/** Test degenerate case p = 0 */
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public void testDegenerate0() throws Exception {
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setDistribution(DistributionFactory.newInstance().createPascalDistribution(5,0.0d));
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setCumulativeTestPoints(new int[] {-1, 0, 1, 5, 10 });
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setCumulativeTestValues(new double[] {0d, 0d, 0d, 0d, 0d});
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setDensityTestPoints(new int[] {-1, 0, 1, 10, 11});
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setDensityTestValues(new double[] {0d, 0d, 0d, 0d, 0d});
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setInverseCumulativeTestPoints(new double[] {0.1d, 0.5d});
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setInverseCumulativeTestValues(new int[] {Integer.MAX_VALUE - 1, Integer.MAX_VALUE - 1});
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verifyDensities();
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verifyCumulativeProbabilities();
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verifyInverseCumulativeProbabilities();
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}
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/** Test degenerate case p = 1 */
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public void testDegenerate1() throws Exception {
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setDistribution(DistributionFactory.newInstance().createPascalDistribution(5,1.0d));
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setCumulativeTestPoints(new int[] {-1, 0, 1, 2, 5, 10 });
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setCumulativeTestValues(new double[] {0d, 1d, 1d, 1d, 1d, 1d});
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setDensityTestPoints(new int[] {-1, 0, 1, 2, 5, 10});
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setDensityTestValues(new double[] {0d, 1d, 0d, 0d, 0d, 0d});
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setInverseCumulativeTestPoints(new double[] {0.1d, 0.5d});
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setInverseCumulativeTestValues(new int[] {-1, -1});
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verifyDensities();
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verifyCumulativeProbabilities();
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verifyInverseCumulativeProbabilities();
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}
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}
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@ -43,6 +43,9 @@ Commons Math Release Notes</title>
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Made ComplexFormat format double values with a provided NumberFormat
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instance instead of using the real part format for all values.
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</action>
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<action dev="psteitz" type="update" issue="38766">
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Added Pascal distribution implementation.
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</action>
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</release>
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<release version="1.1" date="2005-12-17"
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description="This is a maintenance release containing bug fixes and enhancements.
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