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Diffstat (limited to 'src/main/java/org/apache/commons/math/distribution/TDistributionImpl.java')
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diff --git a/src/main/java/org/apache/commons/math/distribution/TDistributionImpl.java b/src/main/java/org/apache/commons/math/distribution/TDistributionImpl.java new file mode 100644 index 0000000..35b72cf --- /dev/null +++ b/src/main/java/org/apache/commons/math/distribution/TDistributionImpl.java @@ -0,0 +1,303 @@ +/* + * 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.special.Gamma; +import org.apache.commons.math.util.FastMath; + +/** + * Default implementation of + * {@link org.apache.commons.math.distribution.TDistribution}. + * + * @version $Revision: 1054524 $ $Date: 2011-01-03 05:59:18 +0100 (lun. 03 janv. 2011) $ + */ +public class TDistributionImpl + extends AbstractContinuousDistribution + implements TDistribution, 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 = -5852615386664158222L; + + /** The degrees of freedom*/ + private double degreesOfFreedom; + + /** Inverse cumulative probability accuracy */ + private final double solverAbsoluteAccuracy; + + /** + * Create a t distribution using the given degrees of freedom and the + * specified inverse cumulative probability absolute accuracy. + * + * @param degreesOfFreedom the degrees of freedom. + * @param inverseCumAccuracy the maximum absolute error in inverse cumulative probability estimates + * (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}) + * @since 2.1 + */ + public TDistributionImpl(double degreesOfFreedom, double inverseCumAccuracy) { + super(); + setDegreesOfFreedomInternal(degreesOfFreedom); + solverAbsoluteAccuracy = inverseCumAccuracy; + } + + /** + * Create a t distribution using the given degrees of freedom. + * @param degreesOfFreedom the degrees of freedom. + */ + public TDistributionImpl(double degreesOfFreedom) { + this(degreesOfFreedom, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); + } + + /** + * Modify the degrees of freedom. + * @param degreesOfFreedom the new degrees of freedom. + * @deprecated as of 2.1 (class will become immutable in 3.0) + */ + @Deprecated + public void setDegreesOfFreedom(double degreesOfFreedom) { + setDegreesOfFreedomInternal(degreesOfFreedom); + } + + /** + * Modify the degrees of freedom. + * @param newDegreesOfFreedom the new degrees of freedom. + */ + private void setDegreesOfFreedomInternal(double newDegreesOfFreedom) { + if (newDegreesOfFreedom <= 0.0) { + throw MathRuntimeException.createIllegalArgumentException( + LocalizedFormats.NOT_POSITIVE_DEGREES_OF_FREEDOM, + newDegreesOfFreedom); + } + this.degreesOfFreedom = newDegreesOfFreedom; + } + + /** + * Access the degrees of freedom. + * @return the degrees of freedom. + */ + public double getDegreesOfFreedom() { + return degreesOfFreedom; + } + + /** + * 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) { + final double n = degreesOfFreedom; + final double nPlus1Over2 = (n + 1) / 2; + return FastMath.exp(Gamma.logGamma(nPlus1Over2) - 0.5 * (FastMath.log(FastMath.PI) + FastMath.log(n)) - + Gamma.logGamma(n/2) - nPlus1Over2 * FastMath.log(1 + x * x /n)); + } + + /** + * For this distribution, X, this method returns P(X < <code>x</code>). + * @param x the value at which the CDF is evaluated. + * @return CDF evaluated at <code>x</code>. + * @throws MathException if the cumulative probability can not be + * computed due to convergence or other numerical errors. + */ + public double cumulativeProbability(double x) throws MathException{ + double ret; + if (x == 0.0) { + ret = 0.5; + } else { + double t = + Beta.regularizedBeta( + degreesOfFreedom / (degreesOfFreedom + (x * x)), + 0.5 * degreesOfFreedom, + 0.5); + if (x < 0.0) { + ret = 0.5 * t; + } else { + ret = 1.0 - 0.5 * t; + } + } + + return ret; + } + + /** + * 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); + } + + /** + * 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) { + return -Double.MAX_VALUE; + } + + /** + * 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) { + return Double.MAX_VALUE; + } + + /** + * 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) { + return 0.0; + } + + /** + * 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; + } + + /** + * 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 mean. + * + * For degrees of freedom parameter df, the mean is + * <ul> + * <li>if <code>df > 1</code> then <code>0</code></li> + * <li>else <code>undefined</code></li> + * </ul> + * + * @return the mean + * @since 2.2 + */ + public double getNumericalMean() { + final double df = getDegreesOfFreedom(); + + if (df > 1) { + return 0; + } + + return Double.NaN; + } + + /** + * Returns the variance. + * + * For degrees of freedom parameter df, the variance is + * <ul> + * <li>if <code>df > 2</code> then <code>df / (df - 2)</code> </li> + * <li>if <code>1 < df <= 2</code> then <code>positive infinity</code></li> + * <li>else <code>undefined</code></li> + * </ul> + * + * @return the variance + * @since 2.2 + */ + public double getNumericalVariance() { + final double df = getDegreesOfFreedom(); + + if (df > 2) { + return df / (df - 2); + } + + if (df > 1 && df <= 2) { + return Double.POSITIVE_INFINITY; + } + + return Double.NaN; + } + +} |