edu.ucla.stat.SOCR.distributions

Class BinomialRandomNDistribution

java.lang.Object

edu.ucla.stat.SOCR.core.SOCRValueSettable

edu.ucla.stat.SOCR.core.Distribution

edu.ucla.stat.SOCR.distributions.BinomialRandomNDistribution

All Implemented Interfaces:

IValueSettable, Pluginable, java.util.Observer

public class BinomialRandomNDistribution
extends Distribution

The binomial distribution with a random number of trials

Field Summary

Fields inherited from class edu.ucla.stat.SOCR.core.Distribution

applet, CONTINUOUS, DISCRETE, MAXMGFXVAL, MAXMGFYVAL, MINMGFXVAL, MIXED, name

Constructor Summary

Constructors

Constructor and Description
BinomialRandomNDistribution() This default constructor: creates a new randomized binomial distribution with probability of success 0.5 and the uniform distribution on {1, 2, 3, 4, 5, 6} for the number of trials
BinomialRandomNDistribution(Distribution d, double p) This general constructor creates a new randomized binomial distribution with a specified probability of success and a specified distribution for the number of trials
BinomialRandomNDistribution(double p) Special constructor: creates a new randomized binomial distribution with a specified probability of success and the uniform distribution on {1, 2, 3, 4, 5, 6} for the number of trials

Method Summary

Methods

Modifier and Type	Method and Description
double	getDensity(double x) The getDensity method is abstract and must be overridden for any specific distribuiton
double	getMean() This method returns a default approximate mean, based on the finite set of domain values.
double	getVariance() This method returns a default approximate variance.
void	setParameters(Distribution d, double p) Set the parameters: the distribution for the number of trials and the probability of success
double	simulate() This method computes a default simulation of a value from the distribution, as a random getQuantile.

Methods inherited from class edu.ucla.stat.SOCR.core.Distribution

addObserver, betaCDF, comb, factorial, findGFRoot, findRoot, gamma, gammaCDF, getCDF, getDisplayPane, getDomain, getFailureRate, getGFDerivative, getGFSecondDerivative, getInstance, getLocalHelp, getMaxDensity, getMean, getMedian, getMGF, getMgfDomain, getName, getOnlineDescription, getPGF, getPGFDomain, getQuantile, getSampleMoment, getSD, getSOCRDistributionFunctors, getSOCRDistributions, getType, getVariance, initialize, inverseCDF, logGamma, paramEstimate, perm, sampleMean, sampleVar, setApplet, setDomain, setDomain, setMGFDomain, setMGFDomain, setMGFParameters, setMGFParameters, setMGFParameters, setMGFParameters, setParameters, setPGFDomain, setPGFDomain, setPGFParameters, setPGFParameters, setPGFParameters, setPGFParameters, update, valueChanged, valueChanged

Methods inherited from class edu.ucla.stat.SOCR.core.SOCRValueSettable

createComponentSetter, createValueSetter, createValueSetter, createValueSetter, createValueSetter, getComponentSetter, getComponentSetters, getValueSetter, getValueSetters

Methods inherited from class java.lang.Object

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

Constructor Detail

BinomialRandomNDistribution

public BinomialRandomNDistribution(Distribution d,
                           double p)

This general constructor creates a new randomized binomial distribution with a specified probability of success and a specified distribution for the number of trials

BinomialRandomNDistribution

public BinomialRandomNDistribution(double p)

Special constructor: creates a new randomized binomial distribution with a specified probability of success and the uniform distribution on {1, 2, 3, 4, 5, 6} for the number of trials

BinomialRandomNDistribution

public BinomialRandomNDistribution()

This default constructor: creates a new randomized binomial distribution with probability of success 0.5 and the uniform distribution on {1, 2, 3, 4, 5, 6} for the number of trials

Method Detail

setParameters

public void setParameters(Distribution d,
                 double p)

Set the parameters: the distribution for the number of trials and the probability of success

getDensity

public double getDensity(double x)

Description copied from class: Distribution

The getDensity method is abstract and must be overridden for any specific distribuiton

Specified by:

getDensity in class Distribution

getMean

public double getMean()

Description copied from class: Distribution

This method returns a default approximate mean, based on the finite set of domain values. This method should be overriden if the mean is known in closed form

Overrides:

getMean in class Distribution

getVariance

public double getVariance()

Description copied from class: Distribution

This method returns a default approximate variance. This method should be overriden if the variance is known in closed form

Overrides:

getVariance in class Distribution

simulate

public double simulate()

Description copied from class: Distribution

This method computes a default simulation of a value from the distribution, as a random getQuantile. This method should be overridden if a better method of simulation is known.

Overrides:

simulate in class Distribution