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