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Diffstat (limited to 'src/main/java/org/apache/commons/math3/distribution/NakagamiDistribution.java')
-rw-r--r-- | src/main/java/org/apache/commons/math3/distribution/NakagamiDistribution.java | 192 |
1 files changed, 192 insertions, 0 deletions
diff --git a/src/main/java/org/apache/commons/math3/distribution/NakagamiDistribution.java b/src/main/java/org/apache/commons/math3/distribution/NakagamiDistribution.java new file mode 100644 index 0000000..298cb30 --- /dev/null +++ b/src/main/java/org/apache/commons/math3/distribution/NakagamiDistribution.java @@ -0,0 +1,192 @@ +/* + * 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.NumberIsTooSmallException; +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.special.Gamma; +import org.apache.commons.math3.util.FastMath; + +/** + * This class implements the Nakagami distribution. + * + * @see <a href="http://en.wikipedia.org/wiki/Nakagami_distribution">Nakagami Distribution + * (Wikipedia)</a> + * @since 3.4 + */ +public class NakagamiDistribution extends AbstractRealDistribution { + + /** Default inverse cumulative probability accuracy. */ + public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9; + + /** Serializable version identifier. */ + private static final long serialVersionUID = 20141003; + + /** The shape parameter. */ + private final double mu; + + /** The scale parameter. */ + private final double omega; + + /** Inverse cumulative probability accuracy. */ + private final double inverseAbsoluteAccuracy; + + /** + * Build a new instance. + * + * <p><b>Note:</b> 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 shape parameter + * @param omega scale parameter (must be positive) + * @throws NumberIsTooSmallException if {@code mu < 0.5} + * @throws NotStrictlyPositiveException if {@code omega <= 0} + */ + public NakagamiDistribution(double mu, double omega) { + this(mu, omega, DEFAULT_INVERSE_ABSOLUTE_ACCURACY); + } + + /** + * Build a new instance. + * + * <p><b>Note:</b> 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 shape parameter + * @param omega scale parameter (must be positive) + * @param inverseAbsoluteAccuracy the maximum absolute error in inverse cumulative probability + * estimates (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}). + * @throws NumberIsTooSmallException if {@code mu < 0.5} + * @throws NotStrictlyPositiveException if {@code omega <= 0} + */ + public NakagamiDistribution(double mu, double omega, double inverseAbsoluteAccuracy) { + this(new Well19937c(), mu, omega, inverseAbsoluteAccuracy); + } + + /** + * Build a new instance. + * + * @param rng Random number generator + * @param mu shape parameter + * @param omega scale parameter (must be positive) + * @param inverseAbsoluteAccuracy the maximum absolute error in inverse cumulative probability + * estimates (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}). + * @throws NumberIsTooSmallException if {@code mu < 0.5} + * @throws NotStrictlyPositiveException if {@code omega <= 0} + */ + public NakagamiDistribution( + RandomGenerator rng, double mu, double omega, double inverseAbsoluteAccuracy) { + super(rng); + + if (mu < 0.5) { + throw new NumberIsTooSmallException(mu, 0.5, true); + } + if (omega <= 0) { + throw new NotStrictlyPositiveException(LocalizedFormats.NOT_POSITIVE_SCALE, omega); + } + + this.mu = mu; + this.omega = omega; + this.inverseAbsoluteAccuracy = inverseAbsoluteAccuracy; + } + + /** + * Access the shape parameter, {@code mu}. + * + * @return the shape parameter. + */ + public double getShape() { + return mu; + } + + /** + * Access the scale parameter, {@code omega}. + * + * @return the scale parameter. + */ + public double getScale() { + return omega; + } + + /** {@inheritDoc} */ + @Override + protected double getSolverAbsoluteAccuracy() { + return inverseAbsoluteAccuracy; + } + + /** {@inheritDoc} */ + public double density(double x) { + if (x <= 0) { + return 0.0; + } + return 2.0 + * FastMath.pow(mu, mu) + / (Gamma.gamma(mu) * FastMath.pow(omega, mu)) + * FastMath.pow(x, 2 * mu - 1) + * FastMath.exp(-mu * x * x / omega); + } + + /** {@inheritDoc} */ + public double cumulativeProbability(double x) { + return Gamma.regularizedGammaP(mu, mu * x * x / omega); + } + + /** {@inheritDoc} */ + public double getNumericalMean() { + return Gamma.gamma(mu + 0.5) / Gamma.gamma(mu) * FastMath.sqrt(omega / mu); + } + + /** {@inheritDoc} */ + public double getNumericalVariance() { + double v = Gamma.gamma(mu + 0.5) / Gamma.gamma(mu); + return omega * (1 - 1 / mu * v * v); + } + + /** {@inheritDoc} */ + public double getSupportLowerBound() { + return 0; + } + + /** {@inheritDoc} */ + public double getSupportUpperBound() { + return Double.POSITIVE_INFINITY; + } + + /** {@inheritDoc} */ + public boolean isSupportLowerBoundInclusive() { + return true; + } + + /** {@inheritDoc} */ + public boolean isSupportUpperBoundInclusive() { + return false; + } + + /** {@inheritDoc} */ + public boolean isSupportConnected() { + return true; + } +} |