jdistlib

Class NonCentralBeta

java.lang.Object

jdistlib.generic.GenericDistribution

jdistlib.NonCentralBeta

public class NonCentralBeta
extends jdistlib.generic.GenericDistribution

Field Summary

Fields

Modifier and Type	Field and Description
protected double	a
protected double	b
protected double	ncp

Fields inherited from class jdistlib.generic.GenericDistribution

random

Constructor Summary

Constructors

Constructor and Description
NonCentralBeta(double a, double b, double ncp)

Method Summary

Methods

Modifier and Type	Method and Description
static double	calculate_ncp(double prob, double x, double a, double b) Given prob, x, a and b, this function returns the corresponding noncentrality parameter of the noncentral beta distribution.
static double	cumulative_raw(double x, double o_x, double a, double b, double ncp)
double	cumulative(double p, boolean lower_tail, boolean log_p)
static double	cumulative(double x, double a, double b, double ncp, boolean lower_tail, boolean log_p)
double	density(double x, boolean log)
static double	density(double x, double a, double b, double ncp, boolean give_log)
double	quantile(double q, boolean lower_tail, boolean log_p)
static double	quantile(double p, double a, double b, double ncp, boolean lower_tail, boolean log_p)
double	random()
static double	random(double a, double b, double ncp, jdistlib.rng.RandomEngine random)
static double[]	random(int n, double a, double b, double ncp, 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

a

protected double a

b

protected double b

ncp

protected double ncp

Constructor Detail

NonCentralBeta

public NonCentralBeta(double a,
              double b,
              double ncp)

Method Detail

density

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

cumulative_raw

public static final double cumulative_raw(double x,
                    double o_x,
                    double a,
                    double b,
                    double ncp)

cumulative

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

quantile

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

random

public static final double random(double a,
            double b,
            double ncp,
            jdistlib.rng.RandomEngine random)

random

public static final double[] random(int n,
              double a,
              double b,
              double ncp,
              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

calculate_ncp

public static final double calculate_ncp(double prob,
                   double x,
                   double a,
                   double b)

Given prob, x, a and b, this function returns the corresponding noncentrality parameter of the noncentral beta distribution. I.e. the following equation I_x(a, b, lambda) = prob is solved for lambda with Newton iteration. This function works just fine when supplied with meaningful input data (and from practically meaningful range) but may easily crash if not. Please be nice.