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Statistical sampling library for use in virtdata libraries, based on apache commons math 4

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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.rng.sampling.distribution;

import org.apache.commons.rng.UniformRandomProvider;

/**
 * Sampling from a Pareto distribution.
 *
 * 

Sampling uses {@link UniformRandomProvider#nextDouble()}.

* * @since 1.0 */ public class InverseTransformParetoSampler extends SamplerBase implements ContinuousSampler { /** Scale. */ private final double scale; /** 1 / Shape. */ private final double oneOverShape; /** Underlying source of randomness. */ private final UniformRandomProvider rng; /** * @param rng Generator of uniformly distributed random numbers. * @param scale Scale of the distribution. * @param shape Shape of the distribution. * @throws IllegalArgumentException if {@code scale <= 0} or {@code shape <= 0} */ public InverseTransformParetoSampler(UniformRandomProvider rng, double scale, double shape) { super(null); if (scale <= 0) { throw new IllegalArgumentException("scale is not strictly positive: " + scale); } if (shape <= 0) { throw new IllegalArgumentException("shape is not strictly positive: " + shape); } this.rng = rng; this.scale = scale; this.oneOverShape = 1 / shape; } /** {@inheritDoc} */ @Override public double sample() { return scale / Math.pow(rng.nextDouble(), oneOverShape); } /** {@inheritDoc} */ @Override public String toString() { return "[Inverse method for Pareto distribution " + rng.toString() + "]"; } }




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