Package jline.lang.processes

Class DiscreteSampler

java.lang.Object

jline.lang.processes.Distribution

jline.lang.processes.DiscreteDistribution

jline.lang.processes.DiscreteSampler

All Implemented Interfaces:

Serializable

public class DiscreteSampler
extends DiscreteDistribution

A class for discrete distributions specified from the probability mass function

See Also:

• Serialized Form

Field Summary

Fields inherited from class jline.lang.processes.Distribution

immediate, mean, name, numParam, params, support

Constructor Summary

Constructors

Constructor	Description
DiscreteSampler(Matrix p)
DiscreteSampler(Matrix p, Matrix x)	Constructs a discrete distribution from a finite probability vector p at the points specified in vector x

Method Summary

Modifier and Type	Method	Description
double	evalCDF(double t)
List<Double>	evalPMF()
Matrix	evalPMF(List<Double> t)
double	getMean()	Computes the distribution mean
double	getSCV()	Computes the distribution squared coefficient of variation (SCV = variance/mean^2)
double	getSkewness()
boolean	isDisabled()
static void	main(String[] args)
double	sample()
double[]	sample(int n)
double[]	sample(int n, Random random)

Methods inherited from class jline.lang.processes.DiscreteDistribution

evalPMF, evalPMF

Methods inherited from class jline.lang.processes.Distribution

evalProbInterval, getName, getNumParams, getParam, getRate, getSupport, getVar, isContinuous, isDiscrete, isImmediate, setNumParams, setParam

Methods inherited from class java.lang.Object

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

Constructor Details

DiscreteSampler

public DiscreteSampler(Matrix p)

DiscreteSampler

public DiscreteSampler(Matrix p,
 Matrix x)

Constructs a discrete distribution from a finite probability vector p at the points specified in vector x

Parameters:

p - - the probability of an item

x - - the value of an item

Method Details

main

public static void main(String[] args)

sample

public double sample()

sample

public double[] sample(int n)

Overrides:

sample in class Distribution

sample

public double[] sample(int n,
 Random random)

Specified by:

sample in class Distribution

getMean

public double getMean()

Computes the distribution mean

Specified by:

getMean in class Distribution

Returns:

- the mean of the distribution

getSCV

public double getSCV()

Computes the distribution squared coefficient of variation (SCV = variance/mean^2)

Specified by:

getSCV in class Distribution

Returns:

getSkewness

public double getSkewness()

Specified by:

getSkewness in class Distribution

evalCDF

public double evalCDF(double t)

Specified by:

evalCDF in class Distribution

evalPMF

public List<Double> evalPMF()

evalPMF

public Matrix evalPMF(List<Double> t)

Overrides:

evalPMF in class DiscreteDistribution

isDisabled

public boolean isDisabled()

Overrides:

isDisabled in class Distribution