Beta.java 

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package blog.distrib;

import blog.*;
import java.util.*;
import common.Util;
A Beta distribution with shape parameters a and b, defined by f(x) =(x^(a-1) (1-x)^(b-1)) / B(a,b) where B(a,b) is a normalization constant equal to integral from 0 to 1 of x^(a-1) (1-x)^(b-1) dx 


public class Beta extends AbstractCondProbDistrib {
Returns a new Beta with shape parameters a and b. 


    public Beta(List params) {
	if (!((params.get(0) instanceof Number) 
	      && (params.get(1) instanceof Number))) {
	    throw new IllegalArgumentException
		("Beta expects two numerical arguments "
		 + "{a, b} where both are Numbers. Got: " + params);
	}
	a = ((Number)params.get(0)).doubleValue();
	b = ((Number)params.get(1)).doubleValue();
	gammaA = new Gamma(a, 1);
	gammaB = new Gamma(b, 1);
    }
Returns the probability of value under this distribution. 


    public double getProb(List args, Object value) {
	if (!(value instanceof Number)) {
	    throw new IllegalArgumentException
		("Beta CPD defines a distribution over objects" 
		 + " of class Number, not " + value.getClass() + ".");
	} else {
	    double x = ((Number)value).doubleValue();
	    return ((Math.pow(x, (a-1)) * Math.pow((1-x), (b-1))) /
		    beta(a, b));
	}
    }
Returns the log of the probability of value under this distribution. 


    public double getLogProb(List args, Object value) {
	if (!(value instanceof Number)) {
	    throw new IllegalArgumentException
		("Beta CPD defines a distribution over objects" 
		 + " of class Number, not " + value.getClass() + ".");
	} else {
	    double x = ((Number)value).doubleValue();
	    return (((a-1)*Math.log(x)) + ((b-1)*Math.log(1 - x))
		    - Math.log(beta(a,b)));
	}
    }
Returns a double sampled according to this distribution. Takes time equivalent to the distrib.Gamma sampling function. (Reference: A Guide To Simulation, 2nd Ed. Bratley, Paul, Bennett L. Fox and Linus E. Schrage.) 


    public Object sampleVal(List args, Type childType) {
	LinkedList l = new LinkedList();
	double y = ((Double)gammaA.sampleVal(l, childType)).doubleValue();
	double z = ((Double)gammaB.sampleVal(l, childType)).doubleValue();
	return new Double( y / (y + z) );
    }
Returns the Beta function of reals a and b B(a,b) = Gamma(a)Gamma(b) / Gamma(a+b) Reference: Numerical Recipes in C http://www.library.cornell.edu/nr/cbookcpdf.html 


    public static double beta(double a, double b) {
	return ((Gamma.gamma(a) * Gamma.gamma(b)) / Gamma.gamma(a+b));
    }

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

    private double a;
    private double b;
    private Gamma gammaA;
    private Gamma gammaB;
}

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