/**
* 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;
import jmt.engine.math.Probability;
import jmt.engine.math.Sfun;
/**
*
* This is the StudentT distribution (for his pdf definition please
* see the constructor description).
*
* <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
* @author Modified by Bertoli Marco, 8/9/2005
*/
public class StudentT extends AbstractDistribution implements Distribution {
/**
* This is the constructor. It creates a new student T distribution which
* is defined from is pdf:
* <pre> G((f+1)/2) 1
* pdf(x)= -------------------- * -------------------------
* (sqrt(pi*f)*G(f/2) (1+((x^2)/f))^((f+1)/2)</pre>
* where G(a) is the gamma (also called "Eulero") function.
* f is called degrees of "freedom".
*/
public StudentT() {
}
/**
* 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.
* @param p parameter of the student T distribution.
* @throws IncorrectDistributionParameterException
* @return double with the probability distribution function evaluated in x.
*/
//OLD
//public double pdf(double x, StudentTPar p)
public double pdf(double x, Parameter p) throws IncorrectDistributionParameterException {
if (p.check()) {
//OLD
//double freedom = p.getFreedom();
double freedom = ((StudentTPar) p).getFreedom();
double val = Sfun.logGamma((freedom + 1) / 2) - Sfun.logGamma(freedom / 2);
double TERM = Math.exp(val) / Math.sqrt(Math.PI * freedom);
return TERM * Math.pow((1 + x * x / freedom), -(freedom + 1) * 0.5);
} else {
throw new IncorrectDistributionParameterException("Remember: the number of degrees of freedom must be an integer 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 student T distribution.
* @throws IncorrectDistributionParameterException
* @return double with the cumulative distribution function evaluated in x.
*/
//OLD
//public double cdf(double x, StudentTPar p)
public double cdf(double x, Parameter p) throws IncorrectDistributionParameterException {
if (p.check()) {
//OLD
//double freedom = p.getFreedom();
double freedom = ((StudentTPar) p).getFreedom();
return Probability.studentT(freedom, x);
} else {
throw new IncorrectDistributionParameterException("Remember: the number of degrees of freedom must be an integer 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 student T distribution.
* @throws IncorrectDistributionParameterException
* @return double with the theoretic mean of the distribution.
*
*/
// the mean of a student T distribution, however, is always 0.
//OLD
//public double theorMean(StudentTPar p)
public double theorMean(Parameter p) throws IncorrectDistributionParameterException {
//alternative implementation may use p.check()
if (p.check()) {
return 0;
} else {
throw new IncorrectDistributionParameterException("");
}
}
/**
* 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 student T distribution.
* @throws IncorrectDistributionParameterException
* @return double with the theoretic variance of the distribution which
* is calculated as n/(n-2) which mean that it makes sense only if n>2; else,
* the variance will be assumed to be 0.
*
*/
//OLD
//public double theorVariance(StudentTPar p)
public double theorVariance(Parameter p) throws IncorrectDistributionParameterException {
if (p.check()) {
//OLD
//double freedom = p.getFreedom();
double freedom = ((StudentTPar) p).getFreedom();
if (freedom < 2) {
return 0;
} else {
return freedom / (freedom - 2);
}
} else {
throw new IncorrectDistributionParameterException("Remember: the number of degrees of freedom must be an integer 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 student T distribution.
* @throws IncorrectDistributionParameterException
* @return double with the next random number of this distribution.
*/
public double nextRand(Parameter p) throws IncorrectDistributionParameterException {
if (p.check()) {
double freedom = ((StudentTPar) p).getFreedom();
double u, v, w;
do {
u = 2.0 * engine.raw() - 1.0;
v = 2.0 * engine.raw() - 1.0;
} while ((w = u * u + v * v) > 1.0);
// If generated number is in the past, reruns this method
double ret = (u * Math.sqrt(freedom * (Math.exp(-2.0 / freedom * Math.log(w)) - 1.0) / w));
return (ret > 0) ? ret : nextRand(p);
} else {
throw new IncorrectDistributionParameterException("Remember: the number of degrees of freedom must be an integer gtz");
}
}
} // end StudentT