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Diffstat (limited to 'src/main/java/org/apache/commons/math/distribution/PascalDistributionImpl.java')
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diff --git a/src/main/java/org/apache/commons/math/distribution/PascalDistributionImpl.java b/src/main/java/org/apache/commons/math/distribution/PascalDistributionImpl.java new file mode 100644 index 0000000..437cbc7 --- /dev/null +++ b/src/main/java/org/apache/commons/math/distribution/PascalDistributionImpl.java @@ -0,0 +1,276 @@ +/* + * 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.math.distribution; + +import java.io.Serializable; + +import org.apache.commons.math.MathException; +import org.apache.commons.math.MathRuntimeException; +import org.apache.commons.math.exception.util.LocalizedFormats; +import org.apache.commons.math.special.Beta; +import org.apache.commons.math.util.MathUtils; +import org.apache.commons.math.util.FastMath; + +/** + * The default implementation of {@link PascalDistribution}. + * @version $Revision: 1054524 $ $Date: 2011-01-03 05:59:18 +0100 (lun. 03 janv. 2011) $ + * @since 1.2 + */ +public class PascalDistributionImpl extends AbstractIntegerDistribution + implements PascalDistribution, Serializable { + + /** Serializable version identifier */ + private static final long serialVersionUID = 6751309484392813623L; + + /** The number of successes */ + private int numberOfSuccesses; + + /** The probability of success */ + private double probabilityOfSuccess; + + /** + * Create a Pascal distribution with the given number of trials and + * probability of success. + * @param r the number of successes + * @param p the probability of success + */ + public PascalDistributionImpl(int r, double p) { + super(); + setNumberOfSuccessesInternal(r); + setProbabilityOfSuccessInternal(p); + } + + /** + * Access the number of successes for this distribution. + * @return the number of successes + */ + public int getNumberOfSuccesses() { + return numberOfSuccesses; + } + + /** + * Access the probability of success for this distribution. + * @return the probability of success + */ + public double getProbabilityOfSuccess() { + return probabilityOfSuccess; + } + + /** + * Change the number of successes for this distribution. + * @param successes the new number of successes + * @throws IllegalArgumentException if <code>successes</code> is not + * positive. + * @deprecated as of 2.1 (class will become immutable in 3.0) + */ + @Deprecated + public void setNumberOfSuccesses(int successes) { + setNumberOfSuccessesInternal(successes); + } + + /** + * Change the number of successes for this distribution. + * @param successes the new number of successes + * @throws IllegalArgumentException if <code>successes</code> is not + * positive. + */ + private void setNumberOfSuccessesInternal(int successes) { + if (successes < 0) { + throw MathRuntimeException.createIllegalArgumentException( + LocalizedFormats.NEGATIVE_NUMBER_OF_SUCCESSES, + successes); + } + numberOfSuccesses = successes; + } + + /** + * Change the probability of success for this distribution. + * @param p the new probability of success + * @throws IllegalArgumentException if <code>p</code> is not a valid + * probability. + * @deprecated as of 2.1 (class will become immutable in 3.0) + */ + @Deprecated + public void setProbabilityOfSuccess(double p) { + setProbabilityOfSuccessInternal(p); + } + + /** + * Change the probability of success for this distribution. + * @param p the new probability of success + * @throws IllegalArgumentException if <code>p</code> is not a valid + * probability. + */ + private void setProbabilityOfSuccessInternal(double p) { + if (p < 0.0 || p > 1.0) { + throw MathRuntimeException.createIllegalArgumentException( + LocalizedFormats.OUT_OF_RANGE_SIMPLE, p, 0.0, 1.0); + } + probabilityOfSuccess = p; + } + + /** + * Access the domain value lower bound, based on <code>p</code>, used to + * bracket a PDF root. + * @param p the desired probability for the critical value + * @return domain value lower bound, i.e. P(X < <i>lower bound</i>) < + * <code>p</code> + */ + @Override + protected int getDomainLowerBound(double p) { + return -1; + } + + /** + * Access the domain value upper bound, based on <code>p</code>, used to + * bracket a PDF root. + * @param p the desired probability for the critical value + * @return domain value upper bound, i.e. P(X < <i>upper bound</i>) > + * <code>p</code> + */ + @Override + protected int getDomainUpperBound(double p) { + // use MAX - 1 because MAX causes loop + return Integer.MAX_VALUE - 1; + } + + /** + * For this distribution, X, this method returns P(X ≤ x). + * @param x the value at which the PDF is evaluated + * @return PDF for this distribution + * @throws MathException if the cumulative probability can not be computed + * due to convergence or other numerical errors + */ + @Override + public double cumulativeProbability(int x) throws MathException { + double ret; + if (x < 0) { + ret = 0.0; + } else { + ret = Beta.regularizedBeta(probabilityOfSuccess, + numberOfSuccesses, x + 1); + } + return ret; + } + + /** + * For this distribution, X, this method returns P(X = x). + * @param x the value at which the PMF is evaluated + * @return PMF for this distribution + */ + public double probability(int x) { + double ret; + if (x < 0) { + ret = 0.0; + } else { + ret = MathUtils.binomialCoefficientDouble(x + + numberOfSuccesses - 1, numberOfSuccesses - 1) * + FastMath.pow(probabilityOfSuccess, numberOfSuccesses) * + FastMath.pow(1.0 - probabilityOfSuccess, x); + } + return ret; + } + + /** + * For this distribution, X, this method returns the largest x, such that + * P(X ≤ x) ≤ <code>p</code>. + * <p> + * Returns <code>-1</code> for p=0 and <code>Integer.MAX_VALUE</code> + * for p=1.</p> + * @param p the desired probability + * @return the largest x such that P(X ≤ x) <= p + * @throws MathException if the inverse cumulative probability can not be + * computed due to convergence or other numerical errors. + * @throws IllegalArgumentException if p < 0 or p > 1 + */ + @Override + public int inverseCumulativeProbability(final double p) + throws MathException { + int ret; + + // handle extreme values explicitly + if (p == 0) { + ret = -1; + } else if (p == 1) { + ret = Integer.MAX_VALUE; + } else { + ret = super.inverseCumulativeProbability(p); + } + + return ret; + } + + /** + * Returns the lower bound of the support for the distribution. + * + * The lower bound of the support is always 0 no matter the parameters. + * + * @return lower bound of the support (always 0) + * @since 2.2 + */ + public int getSupportLowerBound() { + return 0; + } + + /** + * Returns the upper bound of the support for the distribution. + * + * The upper bound of the support is always positive infinity + * no matter the parameters. Positive infinity is represented + * by <code>Integer.MAX_VALUE</code> together with + * {@link #isSupportUpperBoundInclusive()} being <code>false</code> + * + * @return upper bound of the support (always <code>Integer.MAX_VALUE</code> for positive infinity) + * @since 2.2 + */ + public int getSupportUpperBound() { + return Integer.MAX_VALUE; + } + + /** + * Returns the mean. + * + * For number of successes <code>r</code> and + * probability of success <code>p</code>, the mean is + * <code>( r * p ) / ( 1 - p )</code> + * + * @return the mean + * @since 2.2 + */ + public double getNumericalMean() { + final double p = getProbabilityOfSuccess(); + final double r = getNumberOfSuccesses(); + return ( r * p ) / ( 1 - p ); + } + + /** + * Returns the variance. + * + * For number of successes <code>r</code> and + * probability of success <code>p</code>, the mean is + * <code>( r * p ) / ( 1 - p )^2</code> + * + * @return the variance + * @since 2.2 + */ + public double getNumericalVariance() { + final double p = getProbabilityOfSuccess(); + final double r = getNumberOfSuccesses(); + final double pInv = 1 - p; + return ( r * p ) / (pInv * pInv); + } +} |