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/*
* 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.statistics.distribution;
import org.apache.commons.numbers.gamma.Erf;
import org.apache.commons.numbers.gamma.Erfc;
import org.apache.commons.numbers.gamma.InverseErfc;
/**
* This class implements the <a href="http://en.wikipedia.org/wiki/L%C3%A9vy_distribution">
* L&eacute;vy distribution</a>.
*/
public class LevyDistribution extends AbstractContinuousDistribution {
/** Location parameter. */
private final double mu;
/** Scale parameter. */
private final double c;
/** Half of c (for calculations). */
private final double halfC;
/**
* Creates a distribution.
*
* @param mu location
* @param c scale parameter
*/
public LevyDistribution(final double mu,
final double c) {
this.mu = mu;
this.c = c;
this.halfC = 0.5 * c;
}
/** {@inheritDoc}
* <p>
* From Wikipedia: The probability density function of the L&eacute;vy distribution
* over the domain is
* </p>
* <div style="white-space: pre"><code>
* f(x; &mu;, c) = &radic;(c / 2&pi;) * e<sup>-c / 2 (x - &mu;)</sup> / (x - &mu;)<sup>3/2</sup>
* </code></div>
* <p>
* For this distribution, {@code X}, this method returns {@code P(X < x)}.
* If {@code x} is less than location parameter &mu;, {@code 0} is
* returned, as in these cases the distribution is not defined.
* </p>
*/
@Override
public double density(final double x) {
if (x < mu) {
return 0;
}
final double delta = x - mu;
final double f = halfC / delta;
return Math.sqrt(f / Math.PI) * Math.exp(-f) / delta;
}
/** {@inheritDoc}
*
* See documentation of {@link #density(double)} for computation details.
*/
@Override
public double logDensity(double x) {
if (x < mu) {
return Double.NEGATIVE_INFINITY;
}
final double delta = x - mu;
final double f = halfC / delta;
return 0.5 * Math.log(f / Math.PI) - f - Math.log(delta);
}
/** {@inheritDoc}
* <p>
* From Wikipedia: the cumulative distribution function is
* </p>
* <pre>
* f(x; u, c) = erfc (&radic; (c / 2 (x - u )))
* </pre>
*/
@Override
public double cumulativeProbability(final double x) {
if (x < mu) {
return 0;
}
return Erfc.value(Math.sqrt(halfC / (x - mu)));
}
/** {@inheritDoc} */
@Override
public double survivalProbability(final double x) {
if (x < mu) {
return 1;
}
return Erf.value(Math.sqrt(halfC / (x - mu)));
}
/** {@inheritDoc} */
@Override
public double inverseCumulativeProbability(final double p) {
if (p < 0 ||
p > 1) {
throw new DistributionException(DistributionException.INVALID_PROBABILITY, p);
}
final double t = InverseErfc.value(p);
return mu + halfC / (t * t);
}
/**
* Gets the scale parameter of the distribution.
*
* @return scale parameter of the distribution
*/
public double getScale() {
return c;
}
/**
* Gets the location parameter of the distribution.
*
* @return location parameter of the distribution
*/
public double getLocation() {
return mu;
}
/** {@inheritDoc} */
@Override
public double getMean() {
return Double.POSITIVE_INFINITY;
}
/** {@inheritDoc} */
@Override
public double getVariance() {
return Double.POSITIVE_INFINITY;
}
/** {@inheritDoc} */
@Override
public double getSupportLowerBound() {
return getLocation();
}
/** {@inheritDoc} */
@Override
public double getSupportUpperBound() {
return Double.POSITIVE_INFINITY;
}
/** {@inheritDoc} */
@Override
public boolean isSupportConnected() {
return true;
}
}