LognormalDist.java

/*
 * Class:        LognormalDist
 * Description:  lognormal distribution
 * Environment:  Java
 * Software:     SSJ
 * Copyright (C) 2001  Pierre L'Ecuyer and Universite de Montreal
 * Organization: DIRO, Universite de Montreal
 * @author
 * @since
 *
 *
 * 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 umontreal.ssj.probdist;
 
import umontreal.ssj.util.*;

public class LognormalDist extends ContinuousDistribution {
   private double mu;
   private double sigma;

   public LognormalDist() {
      setParams(0.0, 1.0);
   }

   public LognormalDist(double mu, double sigma) {
      setParams(mu, sigma);
   }
 
   public double density(double x) {
      return density(mu, sigma, x);
   }
 
   public double cdf(double x) {
      return cdf(mu, sigma, x);
   }
 
   public double barF(double x) {
      return barF(mu, sigma, x);
   }
 
   public double inverseF(double u) {
      return inverseF(mu, sigma, u);
   }
 
   public double getMean() {
      return LognormalDist.getMean(mu, sigma);
   }
 
   public double getVariance() {
      return LognormalDist.getVariance(mu, sigma);
   }
 
   public double getStandardDeviation() {
      return LognormalDist.getStandardDeviation(mu, sigma);
   }

   public static double density(double mu, double sigma, double x) {
      if (sigma <= 0)
         throw new IllegalArgumentException("sigma <= 0");
      if (x <= 0)
         return 0;
      double diff = Math.log(x) - mu;
      return Math.exp(-diff * diff / (2 * sigma * sigma)) / (Math.sqrt(2 * Math.PI) * sigma * x);
   }

   public static double cdf(double mu, double sigma, double x) {
      if (sigma <= 0.0)
         throw new IllegalArgumentException("sigma  <= 0");
      if (x <= 0.0)
         return 0.0;
      return NormalDist.cdf01((Math.log(x) - mu) / sigma);
   }

   public static double barF(double mu, double sigma, double x) {
      if (sigma <= 0.0)
         throw new IllegalArgumentException("sigma  <= 0");
      if (x <= 0.0)
         return 1.0;
      return NormalDist.barF01((Math.log(x) - mu) / sigma);
   }

   public static double inverseF(double mu, double sigma, double u) {
      double t, v;
 
      if (sigma <= 0.0)
         throw new IllegalArgumentException("sigma  <= 0");
 
      if (u > 1.0 || u < 0.0)
         throw new IllegalArgumentException("u not in [0,1]");
 
      if (Num.DBL_EPSILON >= 1.0 - u)
         return Double.POSITIVE_INFINITY;
 
      if (u <= 0.0)
         return 0.0;
 
      t = NormalDist.inverseF01(u);
      v = mu + sigma * t;
 
      if ((t >= XBIG) || (v >= Num.DBL_MAX_EXP * Num.LN2))
         return Double.POSITIVE_INFINITY;
      if ((t <= -XBIG) || (v <= -Num.DBL_MAX_EXP * Num.LN2))
         return 0.0;
 
      return Math.exp(v);
   }

   public static double[] getMLE(double[] x, int n) {
      if (n <= 0)
         throw new IllegalArgumentException("n <= 0");
 
      final double LN_EPS = Num.LN_DBL_MIN - Num.LN2;
      double parameters[];
      parameters = new double[2];
      double sum = 0.0;
      for (int i = 0; i < n; i++) {
         if (x[i] > 0.0)
            sum += Math.log(x[i]);
         else
            sum += LN_EPS; // log(DBL_MIN / 2)
      }
      parameters[0] = sum / n;
 
      double temp;
      sum = 0.0;
      for (int i = 0; i < n; i++) {
         if (x[i] > 0.0)
            temp = Math.log(x[i]) - parameters[0];
         else
            temp = LN_EPS - parameters[0];
         sum += temp * temp;
      }
      parameters[1] = Math.sqrt(sum / n);
 
      return parameters;
   }

   public static LognormalDist getInstanceFromMLE(double[] x, int n) {
      double parameters[] = getMLE(x, n);
      return new LognormalDist(parameters[0], parameters[1]);
   }

   public static double getMean(double mu, double sigma) {
      if (sigma <= 0.0)
         throw new IllegalArgumentException("sigma <= 0");
 
      return (Math.exp(mu + (sigma * sigma) / 2.0));
   }

   public static double getVariance(double mu, double sigma) {
      if (sigma <= 0.0)
         throw new IllegalArgumentException("sigma <= 0");
 
      return (Math.exp(2.0 * mu + sigma * sigma) * (Math.exp(sigma * sigma) - 1.0));
   }

   public static double getStandardDeviation(double mu, double sigma) {
      return Math.sqrt(LognormalDist.getVariance(mu, sigma));
   }

   public double getMu() {
      return mu;
   }

   public double getSigma() {
      return sigma;
   }

   public void setParams(double mu, double sigma) {
      if (sigma <= 0)
         throw new IllegalArgumentException("sigma <= 0");
      this.mu = mu;
      this.sigma = sigma;
      supportA = 0.0;
   }

   public double[] getParams() {
      double[] retour = { mu, sigma };
      return retour;
   }

   public String toString() {
      return getClass().getSimpleName() + " : mu = " + mu + ", sigma = " + sigma;
   }
 
}