blog.distrib
Class Gamma

java.lang.Object
  blog.AbstractCondProbDistrib
      blog.distrib.Gamma

All Implemented Interfaces:

CondProbDistrib

public class Gamma
extends AbstractCondProbDistrib

A Gamma distribution with shape parameter k and scale parameter 1/lambda. Defined as f(x) = (lambda*e^(-lambda*x)*(lambda*x)^(k - 1)) / Gamma(k) where Gamma(k) = integral from 0 to infinity of t^(k-1) * e^(-t) dt

Constructor Summary

Gamma(double k, double lambda)
Creates a new Gamma distribution with parameters k and lambda.

Gamma(java.util.List params)
Creates a new Gamma distribution with parameters k and lambda.

Method Summary

static double	gamma(double x)
double	getLogProb(java.util.List args, java.lang.Object value) Returns the log of the probability of x under this distribution.
double	getProb(java.util.List args, java.lang.Object value) Returns the probability of x under this distribution
static double	lgamma(double x)
java.lang.Object	sampleVal(java.util.List args, Type childType) Returns a double sampled according to this distribution.

Methods inherited from class blog.AbstractCondProbDistrib

toString

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

Gamma

public Gamma(java.util.List params)

Creates a new Gamma distribution with parameters k and lambda.

Gamma

public Gamma(double k,
             double lambda)

Creates a new Gamma distribution with parameters k and lambda.

Method Detail

getProb

public double getProb(java.util.List args,
                      java.lang.Object value)

Returns the probability of x under this distribution

getLogProb

public double getLogProb(java.util.List args,
                         java.lang.Object value)

Returns the log of the probability of x under this distribution.

Specified by:

getLogProb in interface CondProbDistrib

Overrides:

getLogProb in class AbstractCondProbDistrib

sampleVal

public java.lang.Object sampleVal(java.util.List args,
                                  Type childType)

Returns a double sampled according to this distribution. Uniformly fast for all k > 0. (Reference: Non-Uniform Random Variate Generation, Devroye http://cgm.cs.mcgill.ca/~luc/rnbookindex.html) Uses Cheng's rejection algorithm (GB) for k>=1, rejection from Weibull distribution for 0 < k < 1.

gamma

public static double gamma(double x)

lgamma

public static double lgamma(double x)