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Java example source code file (LogisticDistribution.java)

This example Java source code file (LogisticDistribution.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

abstractrealdistribution, logisticdistribution, outofrangeexception, override, well19937c

The LogisticDistribution.java Java example source code

/*
 * 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.math3.distribution;

import org.apache.commons.math3.exception.NotStrictlyPositiveException;
import org.apache.commons.math3.exception.OutOfRangeException;
import org.apache.commons.math3.exception.util.LocalizedFormats;
import org.apache.commons.math3.random.RandomGenerator;
import org.apache.commons.math3.random.Well19937c;
import org.apache.commons.math3.util.FastMath;
import org.apache.commons.math3.util.MathUtils;

/**
 * This class implements the Logistic distribution.
 *
 * @see <a href="http://en.wikipedia.org/wiki/Logistic_distribution">Logistic Distribution (Wikipedia)
 * @see <a href="http://mathworld.wolfram.com/LogisticDistribution.html">Logistic Distribution (Mathworld)
 *
 * @since 3.4
 */
public class LogisticDistribution extends AbstractRealDistribution {

    /** Serializable version identifier. */
    private static final long serialVersionUID = 20141003;

    /** The location parameter. */
    private final double mu;
    /** The scale parameter. */
    private final double s;

    /**
     * Build a new instance.
     * <p>
     * <b>Note: this constructor will implicitly create an instance of
     * {@link Well19937c} as random generator to be used for sampling only (see
     * {@link #sample()} and {@link #sample(int)}). In case no sampling is
     * needed for the created distribution, it is advised to pass {@code null}
     * as random generator via the appropriate constructors to avoid the
     * additional initialisation overhead.
     *
     * @param mu location parameter
     * @param s scale parameter (must be positive)
     * @throws NotStrictlyPositiveException if {@code beta <= 0}
     */
    public LogisticDistribution(double mu, double s) {
        this(new Well19937c(), mu, s);
    }

    /**
     * Build a new instance.
     *
     * @param rng Random number generator
     * @param mu location parameter
     * @param s scale parameter (must be positive)
     * @throws NotStrictlyPositiveException if {@code beta <= 0}
     */
    public LogisticDistribution(RandomGenerator rng, double mu, double s) {
        super(rng);

        if (s <= 0.0) {
            throw new NotStrictlyPositiveException(LocalizedFormats.NOT_POSITIVE_SCALE, s);
        }

        this.mu = mu;
        this.s = s;
    }

    /**
     * Access the location parameter, {@code mu}.
     *
     * @return the location parameter.
     */
    public double getLocation() {
        return mu;
    }

    /**
     * Access the scale parameter, {@code s}.
     *
     * @return the scale parameter.
     */
    public double getScale() {
        return s;
    }

    /** {@inheritDoc} */
    public double density(double x) {
        double z = (x - mu) / s;
        double v = FastMath.exp(-z);
        return 1 / s * v / ((1.0 + v) * (1.0 + v));
    }

    /** {@inheritDoc} */
    public double cumulativeProbability(double x) {
        double z = 1 / s * (x - mu);
        return 1.0 / (1.0 + FastMath.exp(-z));
    }

    /** {@inheritDoc} */
    @Override
    public double inverseCumulativeProbability(double p) throws OutOfRangeException {
        if (p < 0.0 || p > 1.0) {
            throw new OutOfRangeException(p, 0.0, 1.0);
        } else if (p == 0) {
            return 0.0;
        } else if (p == 1) {
            return Double.POSITIVE_INFINITY;
        }
        return s * Math.log(p / (1.0 - p)) + mu;
    }

    /** {@inheritDoc} */
    public double getNumericalMean() {
        return mu;
    }

    /** {@inheritDoc} */
    public double getNumericalVariance() {
        return (MathUtils.PI_SQUARED / 3.0) * (1.0 / (s * s));
    }

    /** {@inheritDoc} */
    public double getSupportLowerBound() {
        return Double.NEGATIVE_INFINITY;
    }

    /** {@inheritDoc} */
    public double getSupportUpperBound() {
        return Double.POSITIVE_INFINITY;
    }

    /** {@inheritDoc} */
    public boolean isSupportLowerBoundInclusive() {
        return false;
    }

    /** {@inheritDoc} */
    public boolean isSupportUpperBoundInclusive() {
        return false;
    }

    /** {@inheritDoc} */
    public boolean isSupportConnected() {
        return true;
    }

}

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