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Diffstat (limited to 'src/main/java/org/apache/commons/math/distribution/AbstractContinuousDistribution.java')
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diff --git a/src/main/java/org/apache/commons/math/distribution/AbstractContinuousDistribution.java b/src/main/java/org/apache/commons/math/distribution/AbstractContinuousDistribution.java new file mode 100644 index 0000000..aaa2efd --- /dev/null +++ b/src/main/java/org/apache/commons/math/distribution/AbstractContinuousDistribution.java @@ -0,0 +1,231 @@ +/* + * 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.ConvergenceException; +import org.apache.commons.math.MathException; +import org.apache.commons.math.MathRuntimeException; +import org.apache.commons.math.analysis.UnivariateRealFunction; +import org.apache.commons.math.analysis.solvers.BrentSolver; +import org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils; +import org.apache.commons.math.FunctionEvaluationException; +import org.apache.commons.math.exception.util.LocalizedFormats; +import org.apache.commons.math.random.RandomDataImpl; +import org.apache.commons.math.util.FastMath; + +/** + * Base class for continuous distributions. Default implementations are + * provided for some of the methods that do not vary from distribution to + * distribution. + * + * @version $Revision: 1073498 $ $Date: 2011-02-22 21:57:26 +0100 (mar. 22 févr. 2011) $ + */ +public abstract class AbstractContinuousDistribution + extends AbstractDistribution + implements ContinuousDistribution, Serializable { + + /** Serializable version identifier */ + private static final long serialVersionUID = -38038050983108802L; + + /** + * RandomData instance used to generate samples from the distribution + * @since 2.2 + */ + protected final RandomDataImpl randomData = new RandomDataImpl(); + + /** + * Solver absolute accuracy for inverse cumulative computation + * @since 2.1 + */ + private double solverAbsoluteAccuracy = BrentSolver.DEFAULT_ABSOLUTE_ACCURACY; + + /** + * Default constructor. + */ + protected AbstractContinuousDistribution() { + super(); + } + + /** + * Return the probability density for a particular point. + * @param x The point at which the density should be computed. + * @return The pdf at point x. + * @throws MathRuntimeException if the specialized class hasn't implemented this function + * @since 2.1 + */ + public double density(double x) throws MathRuntimeException { + throw new MathRuntimeException(new UnsupportedOperationException(), + LocalizedFormats.NO_DENSITY_FOR_THIS_DISTRIBUTION); + } + + /** + * For this distribution, X, this method returns the critical point x, such + * that P(X < x) = <code>p</code>. + * + * @param p the desired probability + * @return x, such that P(X < x) = <code>p</code> + * @throws MathException if the inverse cumulative probability can not be + * computed due to convergence or other numerical errors. + * @throws IllegalArgumentException if <code>p</code> is not a valid + * probability. + */ + public double inverseCumulativeProbability(final double p) + throws MathException { + if (p < 0.0 || p > 1.0) { + throw MathRuntimeException.createIllegalArgumentException( + LocalizedFormats.OUT_OF_RANGE_SIMPLE, p, 0.0, 1.0); + } + + // by default, do simple root finding using bracketing and default solver. + // subclasses can override if there is a better method. + UnivariateRealFunction rootFindingFunction = + new UnivariateRealFunction() { + public double value(double x) throws FunctionEvaluationException { + double ret = Double.NaN; + try { + ret = cumulativeProbability(x) - p; + } catch (MathException ex) { + throw new FunctionEvaluationException(x, ex.getSpecificPattern(), ex.getGeneralPattern(), ex.getArguments()); + } + if (Double.isNaN(ret)) { + throw new FunctionEvaluationException(x, LocalizedFormats.CUMULATIVE_PROBABILITY_RETURNED_NAN, x, p); + } + return ret; + } + }; + + // Try to bracket root, test domain endpoints if this fails + double lowerBound = getDomainLowerBound(p); + double upperBound = getDomainUpperBound(p); + double[] bracket = null; + try { + bracket = UnivariateRealSolverUtils.bracket( + rootFindingFunction, getInitialDomain(p), + lowerBound, upperBound); + } catch (ConvergenceException ex) { + /* + * Check domain endpoints to see if one gives value that is within + * the default solver's defaultAbsoluteAccuracy of 0 (will be the + * case if density has bounded support and p is 0 or 1). + */ + if (FastMath.abs(rootFindingFunction.value(lowerBound)) < getSolverAbsoluteAccuracy()) { + return lowerBound; + } + if (FastMath.abs(rootFindingFunction.value(upperBound)) < getSolverAbsoluteAccuracy()) { + return upperBound; + } + // Failed bracket convergence was not because of corner solution + throw new MathException(ex); + } + + // find root + double root = UnivariateRealSolverUtils.solve(rootFindingFunction, + // override getSolverAbsoluteAccuracy() to use a Brent solver with + // absolute accuracy different from BrentSolver default + bracket[0],bracket[1], getSolverAbsoluteAccuracy()); + return root; + } + + /** + * Reseeds the random generator used to generate samples. + * + * @param seed the new seed + * @since 2.2 + */ + public void reseedRandomGenerator(long seed) { + randomData.reSeed(seed); + } + + /** + * Generates a random value sampled from this distribution. The default + * implementation uses the + * <a href="http://en.wikipedia.org/wiki/Inverse_transform_sampling"> inversion method.</a> + * + * @return random value + * @since 2.2 + * @throws MathException if an error occurs generating the random value + */ + public double sample() throws MathException { + return randomData.nextInversionDeviate(this); + } + + /** + * Generates a random sample from the distribution. The default implementation + * generates the sample by calling {@link #sample()} in a loop. + * + * @param sampleSize number of random values to generate + * @since 2.2 + * @return an array representing the random sample + * @throws MathException if an error occurs generating the sample + * @throws IllegalArgumentException if sampleSize is not positive + */ + public double[] sample(int sampleSize) throws MathException { + if (sampleSize <= 0) { + MathRuntimeException.createIllegalArgumentException(LocalizedFormats.NOT_POSITIVE_SAMPLE_SIZE, sampleSize); + } + double[] out = new double[sampleSize]; + for (int i = 0; i < sampleSize; i++) { + out[i] = sample(); + } + return out; + } + + /** + * Access the initial domain value, based on <code>p</code>, used to + * bracket a CDF root. This method is used by + * {@link #inverseCumulativeProbability(double)} to find critical values. + * + * @param p the desired probability for the critical value + * @return initial domain value + */ + protected abstract double getInitialDomain(double p); + + /** + * Access the domain value lower bound, based on <code>p</code>, used to + * bracket a CDF root. This method is used by + * {@link #inverseCumulativeProbability(double)} to find critical values. + * + * @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> + */ + protected abstract double getDomainLowerBound(double p); + + /** + * Access the domain value upper bound, based on <code>p</code>, used to + * bracket a CDF root. This method is used by + * {@link #inverseCumulativeProbability(double)} to find critical values. + * + * @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> + */ + protected abstract double getDomainUpperBound(double p); + + /** + * Returns the solver absolute accuracy for inverse cumulative computation. + * + * @return the maximum absolute error in inverse cumulative probability estimates + * @since 2.1 + */ + protected double getSolverAbsoluteAccuracy() { + return solverAbsoluteAccuracy; + } + +} |