/**
* Copyright (C) 2006, Laboratorio di Valutazione delle Prestazioni - Politecnico di Milano
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
*/
package jmt.engine.random;
import jmt.common.exception.IncorrectDistributionParameterException;
/**
*
* This is the Pareto distribution (see the constructor description
* for his pdf definition).
*
* <br><br>Copyright (c) 2003
* <br>Politecnico di Milano - dipartimento di Elettronica e Informazione
* @author Fabrizio Frontera - ffrontera@yahoo.it
* @author Modified by Stefano Omini, 7/5/2004
*/
public class Pareto extends AbstractDistribution implements Distribution {
/**
* This is the constructor. It creates a new empty pareto distribution which
* is defined from is pdf:
* <pre> alpha (-(alpha+1))
* pdf(x) = alpha * k * x</pre>
* with alpha gtz and k gtz and less or equal to x
*/
public Pareto() {
}
/**
* it returns the pdf of the distribution.
* This method is used to obtain from the distribution his probability distribution
* function evaluated where required by the user.
*
* @param x double indicating where to evaluate the pdf. Must be > alpha
* @param p parameter of the pareto distribution.
* @throws IncorrectDistributionParameterException
* @return double with the probability distribution function evaluated in x.
*/
//OLD
//public double pdf(double x, ParetoPar p)
public double pdf(double x, Parameter p) throws IncorrectDistributionParameterException {
if (p.check()) {
//OLD
//double alfa = p.getAlpha();
//double k = p.getK();
double alfa = ((ParetoPar) p).getAlpha();
double k = ((ParetoPar) p).getK();
if (x <= alfa) {
throw new IncorrectDistributionParameterException("Error: x must be >alpha.");
}
return (alfa * Math.pow(k, alfa) / Math.pow(x, (alfa + 1)));
} else {
throw new IncorrectDistributionParameterException("Remember: parameter alpha and k must be gtz");
}
}
/**
* it returns the cdf of the distribution.
* This method is used to obtain from the distribution his cumulative distribution
* function evaluated where required by the user.
*
* @param x double indicating where to evaluate the cdf.
* @param p parameter of the pareto distribution.
* @throws IncorrectDistributionParameterException
* @return double with the cumulative distribution function evaluated in x.
*/
//OLD
//public double cdf(double x, ParetoPar p)
public double cdf(double x, Parameter p) throws IncorrectDistributionParameterException {
if (p.check()) {
//OLD
//double alfa = p.getAlpha();
//double k = p.getK();
double alfa = ((ParetoPar) p).getAlpha();
double k = ((ParetoPar) p).getK();
if (x <= alfa) {
return 0.0;
}
return 1.0 - Math.pow((k / x), alfa);
} else {
throw new IncorrectDistributionParameterException("Remember: parameter alpha and k must be gtz");
}
}
/**
* it returns the mean of the distribution.
* This method is used to obtain from the distribution the value of his own
* theoretic mean.
*
* @param p parameter of the pareto distribution.
* @throws IncorrectDistributionParameterException
* @return double with the theoretic mean of the distribution.
*
* the mean is calculated as: (k*alpha)/(alpha-1)
*/
//OLD
//public double theorMean(ParetoPar p)
public double theorMean(Parameter p) throws IncorrectDistributionParameterException {
if (p.check()) {
//OLD
//double alfa = p.getAlpha();
//double k = p.getK();
double alfa = ((ParetoPar) p).getAlpha();
double k = ((ParetoPar) p).getK();
return (alfa * k / (alfa - 1));
} else {
throw new IncorrectDistributionParameterException("Remember: parameter alpha and k must be gtz");
}
}
/**
* it returns the variance of the distribution.
* This method is used to obtain from the distribution his own theoretical
* variance.
*
* @param p parameter of the pareto distribution.
* @throws IncorrectDistributionParameterException
* @return double with the theoretic variance of the distribution.
*
* the variance is calculated as: ((alpha*(k^2))/(((alpha-1)^2)*(alpha-2)))
*/
//OLD
//public double theorVariance(ParetoPar p)
public double theorVariance(Parameter p) throws IncorrectDistributionParameterException {
if (p.check()) {
//OLD
//double alfa = p.getAlpha();
//double k = p.getK();
double alfa = ((ParetoPar) p).getAlpha();
double k = ((ParetoPar) p).getK();
return (alfa * k * k / ((alfa - 1) * (alfa - 1) * (alfa - 2)));
} else {
throw new IncorrectDistributionParameterException("Remember: parameter alpha and k must be gtz");
}
}
/**
* it returns the new random number.
* This method is used to obtain from the distribution the next number distributed
* according to the distribution parameter.
*
* @param p parameter of the pareto distribution.
* @throws IncorrectDistributionParameterException
* @return double with the next random number of this distribution.
*/
public double nextRand(Parameter p) throws IncorrectDistributionParameterException {
if (p.check()) {
double alpha = ((ParetoPar) p).getAlpha();
double k = ((ParetoPar) p).getK();
return Math.pow((1 - engine.raw()), (-1 / alpha)) * k;
} else {
throw new IncorrectDistributionParameterException("Remember: parameter alpha and k must be gtz");
}
}
} // end Pareto