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Diffstat (limited to 'src/main/java/org/apache/commons/math/distribution/NormalDistributionImpl.java')
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diff --git a/src/main/java/org/apache/commons/math/distribution/NormalDistributionImpl.java b/src/main/java/org/apache/commons/math/distribution/NormalDistributionImpl.java new file mode 100644 index 0000000..1164649 --- /dev/null +++ b/src/main/java/org/apache/commons/math/distribution/NormalDistributionImpl.java @@ -0,0 +1,349 @@ +/* + * 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.Erf; +import org.apache.commons.math.util.FastMath; + +/** + * Default implementation of + * {@link org.apache.commons.math.distribution.NormalDistribution}. + * + * @version $Revision: 1054524 $ $Date: 2011-01-03 05:59:18 +0100 (lun. 03 janv. 2011) $ + */ +public class NormalDistributionImpl extends AbstractContinuousDistribution + implements NormalDistribution, Serializable { + + /** + * Default inverse cumulative probability accuracy + * @since 2.1 + */ + public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9; + + /** Serializable version identifier */ + private static final long serialVersionUID = 8589540077390120676L; + + /** &sqrt;(2 π) */ + private static final double SQRT2PI = FastMath.sqrt(2 * FastMath.PI); + + /** The mean of this distribution. */ + private double mean = 0; + + /** The standard deviation of this distribution. */ + private double standardDeviation = 1; + + /** Inverse cumulative probability accuracy */ + private final double solverAbsoluteAccuracy; + + /** + * Create a normal distribution using the given mean and standard deviation. + * @param mean mean for this distribution + * @param sd standard deviation for this distribution + */ + public NormalDistributionImpl(double mean, double sd){ + this(mean, sd, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); + } + + /** + * Create a normal distribution using the given mean, standard deviation and + * inverse cumulative distribution accuracy. + * + * @param mean mean for this distribution + * @param sd standard deviation for this distribution + * @param inverseCumAccuracy inverse cumulative probability accuracy + * @since 2.1 + */ + public NormalDistributionImpl(double mean, double sd, double inverseCumAccuracy) { + super(); + setMeanInternal(mean); + setStandardDeviationInternal(sd); + solverAbsoluteAccuracy = inverseCumAccuracy; + } + + /** + * Creates normal distribution with the mean equal to zero and standard + * deviation equal to one. + */ + public NormalDistributionImpl(){ + this(0.0, 1.0); + } + + /** + * Access the mean. + * @return mean for this distribution + */ + public double getMean() { + return mean; + } + + /** + * Modify the mean. + * @param mean for this distribution + * @deprecated as of 2.1 (class will become immutable in 3.0) + */ + @Deprecated + public void setMean(double mean) { + setMeanInternal(mean); + } + + /** + * Modify the mean. + * @param newMean for this distribution + */ + private void setMeanInternal(double newMean) { + this.mean = newMean; + } + + /** + * Access the standard deviation. + * @return standard deviation for this distribution + */ + public double getStandardDeviation() { + return standardDeviation; + } + + /** + * Modify the standard deviation. + * @param sd standard deviation for this distribution + * @throws IllegalArgumentException if <code>sd</code> is not positive. + * @deprecated as of 2.1 (class will become immutable in 3.0) + */ + @Deprecated + public void setStandardDeviation(double sd) { + setStandardDeviationInternal(sd); + } + + /** + * Modify the standard deviation. + * @param sd standard deviation for this distribution + * @throws IllegalArgumentException if <code>sd</code> is not positive. + */ + private void setStandardDeviationInternal(double sd) { + if (sd <= 0.0) { + throw MathRuntimeException.createIllegalArgumentException( + LocalizedFormats.NOT_POSITIVE_STANDARD_DEVIATION, + sd); + } + standardDeviation = sd; + } + + /** + * 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. + * @deprecated + */ + @Deprecated + public double density(Double x) { + return density(x.doubleValue()); + } + + /** + * Returns the probability density for a particular point. + * + * @param x The point at which the density should be computed. + * @return The pdf at point x. + * @since 2.1 + */ + @Override + public double density(double x) { + double x0 = x - mean; + return FastMath.exp(-x0 * x0 / (2 * standardDeviation * standardDeviation)) / (standardDeviation * SQRT2PI); + } + + /** + * For this distribution, X, this method returns P(X < <code>x</code>). + * If <code>x</code>is more than 40 standard deviations from the mean, 0 or 1 is returned, + * as in these cases the actual value is within <code>Double.MIN_VALUE</code> of 0 or 1. + * + * @param x the value at which the CDF is evaluated. + * @return CDF evaluated at <code>x</code>. + * @throws MathException if the algorithm fails to converge + */ + public double cumulativeProbability(double x) throws MathException { + final double dev = x - mean; + if (FastMath.abs(dev) > 40 * standardDeviation) { + return dev < 0 ? 0.0d : 1.0d; + } + return 0.5 * (1.0 + Erf.erf(dev / + (standardDeviation * FastMath.sqrt(2.0)))); + } + + /** + * Return the absolute accuracy setting of the solver used to estimate + * inverse cumulative probabilities. + * + * @return the solver absolute accuracy + * @since 2.1 + */ + @Override + protected double getSolverAbsoluteAccuracy() { + return solverAbsoluteAccuracy; + } + + /** + * For this distribution, X, this method returns the critical point x, such + * that P(X < x) = <code>p</code>. + * <p> + * Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and + * <code>Double.POSITIVE_INFINITY</code> for p=1.</p> + * + * @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. + */ + @Override + public double inverseCumulativeProbability(final double p) + throws MathException { + if (p == 0) { + return Double.NEGATIVE_INFINITY; + } + if (p == 1) { + return Double.POSITIVE_INFINITY; + } + return super.inverseCumulativeProbability(p); + } + + /** + * Generates a random value sampled from this distribution. + * + * @return random value + * @since 2.2 + * @throws MathException if an error occurs generating the random value + */ + @Override + public double sample() throws MathException { + return randomData.nextGaussian(mean, standardDeviation); + } + + /** + * 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> + */ + @Override + protected double getDomainLowerBound(double p) { + double ret; + + if (p < .5) { + ret = -Double.MAX_VALUE; + } else { + ret = mean; + } + + return ret; + } + + /** + * 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> + */ + @Override + protected double getDomainUpperBound(double p) { + double ret; + + if (p < .5) { + ret = mean; + } else { + ret = Double.MAX_VALUE; + } + + return ret; + } + + /** + * 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 + */ + @Override + protected double getInitialDomain(double p) { + double ret; + + if (p < .5) { + ret = mean - standardDeviation; + } else if (p > .5) { + ret = mean + standardDeviation; + } else { + ret = mean; + } + + return ret; + } + + /** + * Returns the lower bound of the support for the distribution. + * + * The lower bound of the support is always negative infinity + * no matter the parameters. + * + * @return lower bound of the support (always Double.NEGATIVE_INFINITY) + * @since 2.2 + */ + public double getSupportLowerBound() { + return Double.NEGATIVE_INFINITY; + } + + /** + * Returns the upper bound of the support for the distribution. + * + * The upper bound of the support is always positive infinity + * no matter the parameters. + * + * @return upper bound of the support (always Double.POSITIVE_INFINITY) + * @since 2.2 + */ + public double getSupportUpperBound() { + return Double.POSITIVE_INFINITY; + } + + /** + * Returns the variance. + * + * For standard deviation parameter <code>s</code>, + * the variance is <code>s^2</code> + * + * @return the variance + * @since 2.2 + */ + public double getNumericalVariance() { + final double s = getStandardDeviation(); + return s * s; + } +} |