jdistlib

Class NonCentralChiSquare

java.lang.Object

jdistlib.generic.GenericDistribution

jdistlib.NonCentralChiSquare

public class NonCentralChiSquare
extends jdistlib.generic.GenericDistribution

Field Summary

Fields

Modifier and Type	Field and Description
protected double	df
protected double	ncp

Fields inherited from class jdistlib.generic.GenericDistribution

random

Constructor Summary

Constructors

Constructor and Description
NonCentralChiSquare(double df, double ncp)

Method Summary

Modifier and Type	Method and Description
static double	cumulative_raw(double x, double f, double theta, double errmax, double reltol, int itrmax, boolean lower_tail, boolean log_p)
double	cumulative(double p, boolean lower_tail, boolean log_p)
static double	cumulative(double x, double df, double ncp, boolean lower_tail, boolean log_p)
double	density(double x, boolean log)
static double	density(double x, double df, double ncp, boolean give_log)
double	quantile(double q, boolean lower_tail, boolean log_p)
static double	quantile(double p, double df, double ncp, boolean lower_tail, boolean log_p)
double	random()
static double	random(double df, double lambda, jdistlib.rng.RandomEngine random) According to Hans R.
static double[]	random(int n, double df, double lambda, jdistlib.rng.RandomEngine random)

Methods inherited from class jdistlib.generic.GenericDistribution

cumulative_hazard, cumulative_hazard, cumulative, cumulative, cumulative, density, density, getRandomEngine, hazard, hazard, inverse_survival, inverse_survival, quantile, quantile, quantile, random, random, setRandomEngine, survival, survival, survival

Methods inherited from class java.lang.Object

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

Field Detail

df

protected double df

ncp

protected double ncp

Constructor Detail

NonCentralChiSquare

public NonCentralChiSquare(double df,
                           double ncp)

Method Detail

density

public static final double density(double x,
                                   double df,
                                   double ncp,
                                   boolean give_log)

cumulative_raw

public static final double cumulative_raw(double x,
                                          double f,
                                          double theta,
                                          double errmax,
                                          double reltol,
                                          int itrmax,
                                          boolean lower_tail,
                                          boolean log_p)

cumulative

public static final double cumulative(double x,
                                      double df,
                                      double ncp,
                                      boolean lower_tail,
                                      boolean log_p)

quantile

public static final double quantile(double p,
                                    double df,
                                    double ncp,
                                    boolean lower_tail,
                                    boolean log_p)

random

public static final double random(double df,
                                  double lambda,
                                  jdistlib.rng.RandomEngine random)

         According to Hans R. Kuensch's suggestion (30 sep 2002):

          It should be easy to do the general case (ncp > 0) by decomposing it
          as the sum of a central chisquare with df degrees of freedom plus a
          noncentral chisquare with zero degrees of freedom (which is a Poisson
          mixture of central chisquares with integer degrees of freedom),
          see Formula (29.5b-c) in Johnson, Kotz, Balakrishnan (1995).

          The noncentral chisquare with arbitary degrees of freedom is of interest
          for simulating the Cox-Ingersoll-Ross model for interest rates in
          finance.

          R code that works is

            rchisq0 <- function(n, ncp) {
                p <- 0 < (K <- rpois(n, lambda = ncp / 2))
                r <- numeric(n)
                r[p] <- rchisq(sum(p), df = 2*K[p])
                r
            }

            rchisq <- function(n, df, ncp=0) {
                if(missing(ncp)) .Internal(rchisq(n, df))
                else rchisq0(n, ncp) + .Internal(rchisq(n, df))
            }

random

public static final double[] random(int n,
                                    double df,
                                    double lambda,
                                    jdistlib.rng.RandomEngine random)

density

public double density(double x,
                      boolean log)

Specified by:

density in class jdistlib.generic.GenericDistribution

cumulative

public double cumulative(double p,
                         boolean lower_tail,
                         boolean log_p)

Specified by:

cumulative in class jdistlib.generic.GenericDistribution

quantile

public double quantile(double q,
                       boolean lower_tail,
                       boolean log_p)

Specified by:

quantile in class jdistlib.generic.GenericDistribution

random

public double random()

Specified by:

random in class jdistlib.generic.GenericDistribution