NegativeBinomial.java 

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package blog.distrib;

import blog.*;
import java.util.*;
import common.Util;
A Negative Binomial distribution with parameters k (number of successes) and p (probability of a success at a given trial). If k is an integer, this is also called the Pascal distribution. The distribution is defined (in discrete terms) as the number of failures before k successes. 


public class NegativeBinomial extends AbstractCondProbDistrib {
Creates a new instance of the NegativeBinomial with parameters k and p. 


    public NegativeBinomial(List params) {
	if (!((params.get(0) instanceof Integer) 
	      && (params.get(1) instanceof Number))) {
	    throw new IllegalArgumentException
		("NegativeBinomial expects two numerical arguments "
		 + "{k, p} where k is an Integer, p a Double. Got: " + params);
	}
	k = ((Integer)params.get(0)).intValue();
	p = ((Number)params.get(1)).doubleValue();
	gamma = new Gamma(k, (p / (1-p)));
    }
Returns the probability of n failures under this distribution. 


    public double getProb (List args, Object value) {
	if (!(value instanceof Integer)) {
	    throw new IllegalArgumentException
		("NegativeBinomial CPD defines a distribution over objects" 
		 + " of class Integer, not " + value.getClass() + ".");
	} 
	int n = ((Integer)value).intValue();
	// Return C(k+n-1, n)*p^k*(1-p)^n
	return Math.exp(getLogProb(args, value));
    }
Returns the log of the probability of n failures in this distribution. 


    public double getLogProb (List args, Object value) {
	if (!(value instanceof Integer)) {
	    throw new IllegalArgumentException
		("NegativeBinomial CPD defines a distribution over objects" 
		 + " of class Integer, not " + value.getClass() + ".");
	} 
	int n = ((Integer)value).intValue();
	// Return log (C(k+n-1, n)*p^k*(1-p)^n)
	return (k*Math.log(p) + n*Math.log(1 - p)
		+ Math.log(Util.factorial(n + k - 1))
		- Math.log(Util.factorial(k - 1))
		- Math.log(Util.factorial(n)));
    }
Returns a double sampled according to this distribution. Takes time O(GammaDistrib.sampleVal() + Poisson.sampleVal()). (Reference: A Guide To Simulation, 2nd Ed. Bratley, Paul, Bennett L. Fox and Linus E. Schrage.) 


    public Object sampleVal(List args, Type childType) {
	Double theta = (Double)gamma.sampleVal(new LinkedList(), childType);
	LinkedList l = new LinkedList();
	l.add(theta);
	Poisson poisson = new Poisson(l);
	return poisson.sampleVal(new LinkedList(), childType);
    }

    public String toString() {
	return getClass().getName();
    }

    private Gamma gamma;
    private int k;
    private double p;
}

This file was generated on Tue Jun 08 17:53:47 PDT 2010 from file NegativeBinomial.java
by the ilog.language.tools.Hilite Java tool written by Hassan Aït-Kaci