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/*
 * Copyright 2015 SPZ
 *
 * Licensed 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 math.stats.distribution;

import math.FastMath;
import math.rng.DefaultRng;
import math.rng.PseudoRandom;
import math.stats.ProbabilityFuncs;

/**
 * TODO
 * 

* https://en.wikipedia.org/wiki/Log-normal_distribution */ public class LogNormal extends AbstractContinuousDistribution { private final double mu; private final double sigma; public LogNormal(PseudoRandom prng, double mu, double sigma) { super(prng); if (sigma <= 0.0) { throw new IllegalArgumentException("sigma <= 0.0 : " + sigma); } this.mu = mu; this.sigma = sigma; } public LogNormal(double mu, double sigma) { this(DefaultRng.newPseudoRandom(), mu, sigma); } @Override public double pdf(double x) { if (x <= 0.0) { return 0.0; } double d = Math.log(x) - mu; return FastMath.exp((-d * d) / (2.0 * (sigma * sigma))) / (Math.sqrt(2.0 * Math.PI) * sigma * x); } @Override public double cdf(double x) { if (x <= 0.0) { return 0.0; } return ProbabilityFuncs.normal((Math.log(x) - mu) / sigma); } @Override public double mean() { return (FastMath.exp(mu + (sigma * sigma) / 2.0)); } @Override public double variance() { double sigsig = sigma * sigma; return ((FastMath.exp(2.0 * mu + sigsig) * (FastMath.exp(sigsig) - 1.0))); } @Override public double sample() { double stdNormal = prng.nextGaussian(); return FastMath.exp(mu + sigma * stdNormal); } @Override public String toString() { return getSimpleName(mu, sigma); } }





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