| /* |
| * 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); |
| } |
| } |