LevyDistribution.java
/*
* 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
*
* https://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.
*/
/*
* This is not the original file distributed by the Apache Software Foundation
* It has been modified by the Hipparchus project
*/
package org.hipparchus.distribution.continuous;
import org.hipparchus.exception.MathIllegalArgumentException;
import org.hipparchus.special.Erf;
import org.hipparchus.util.FastMath;
import org.hipparchus.util.MathUtils;
/**
* This class implements the <a href="http://en.wikipedia.org/wiki/L%C3%A9vy_distribution">
* Lévy distribution</a>.
*/
public class LevyDistribution extends AbstractRealDistribution {
/** Serializable UID. */
private static final long serialVersionUID = 20130314L;
/** Location parameter. */
private final double mu;
/** Scale parameter. */
private final double c; // Setting this to 1 returns a cumProb of 1.0
/** Half of c (for calculations). */
private final double halfC;
/**
* Build a new instance.
*
* @param mu location parameter
* @param c scale parameter
*/
public LevyDistribution(final double mu, final double c) {
super();
this.mu = mu;
this.c = c;
this.halfC = 0.5 * c;
}
/** {@inheritDoc}
* <p>
* From Wikipedia: The probability density function of the Lévy distribution
* over the domain is
* </p>
* \[
* f(x; \mu, c) = \sqrt{\frac{c}{2\pi}} \frac{e^{\frac{-c}{2 (x - \mu)}}}{(x - \mu)^\frac{3}{2}}
* \]
* <p>
* For this distribution, {@code X}, this method returns {@code P(X < x)}.
* If {@code x} is less than location parameter μ, {@code Double.NaN} is
* returned, as in these cases the distribution is not defined.
* </p>
*/
@Override
public double density(final double x) {
if (x < mu) {
return Double.NaN;
}
final double delta = x - mu;
final double f = halfC / delta;
return FastMath.sqrt(f / FastMath.PI) * FastMath.exp(-f) /delta;
}
/** {@inheritDoc}
*
* See documentation of {@link #density(double)} for computation details.
*/
@Override
public double logDensity(double x) {
if (x < mu) {
return Double.NaN;
}
final double delta = x - mu;
final double f = halfC / delta;
return 0.5 * FastMath.log(f / FastMath.PI) - f - FastMath.log(delta);
}
/** {@inheritDoc}
* <p>
* From Wikipedia: the cumulative distribution function is
* </p>
* <pre>
* f(x; u, c) = erfc (√ (c / 2 (x - u )))
* </pre>
*/
@Override
public double cumulativeProbability(final double x) {
if (x < mu) {
return Double.NaN;
}
return Erf.erfc(FastMath.sqrt(halfC / (x - mu)));
}
/** {@inheritDoc} */
@Override
public double inverseCumulativeProbability(final double p) throws MathIllegalArgumentException {
MathUtils.checkRangeInclusive(p, 0, 1);
final double t = Erf.erfcInv(p);
return mu + halfC / (t * t);
}
/** Get the scale parameter of the distribution.
* @return scale parameter of the distribution
*/
public double getScale() {
return c;
}
/** Get the location parameter of the distribution.
* @return location parameter of the distribution
*/
public double getLocation() {
return mu;
}
/** {@inheritDoc} */
@Override
public double getNumericalMean() {
return Double.POSITIVE_INFINITY;
}
/** {@inheritDoc} */
@Override
public double getNumericalVariance() {
return Double.POSITIVE_INFINITY;
}
/** {@inheritDoc} */
@Override
public double getSupportLowerBound() {
return mu;
}
/** {@inheritDoc} */
@Override
public double getSupportUpperBound() {
return Double.POSITIVE_INFINITY;
}
/** {@inheritDoc} */
@Override
public boolean isSupportConnected() {
return true;
}
}