edu.uah.math.distributions
Class HypergeometricDistribution

java.lang.Object
  edu.uah.math.distributions.Distribution
      edu.uah.math.distributions.HypergeometricDistribution

All Implemented Interfaces:

java.io.Serializable

public class HypergeometricDistribution
extends Distribution
implements java.io.Serializable

This class models the hypergeometric distribution with a specified population size, sample size, and number of type 1 objects. This is the distribution of the number of type 1 objects in a sample chosen without replacement from a finite, two-type population.

Version:

August, 2003

Author:

Kyle Siegrist, Dawn Duehring

See Also:

Serialized Form

Field Summary

Fields inherited from class edu.uah.math.distributions.Distribution

CONTINUOUS, DISCRETE, MIXED

Constructor Summary

HypergeometricDistribution()
This default constructor: creates a new hypergeometric distribuiton with population 100 containing 50 type 1 objects, and with sample size 10.

HypergeometricDistribution(int m, int r, int n)
This general constructor creates a new hypergeometric distribution with specified values of the parameters.

Method Summary

double	getDensity(double x) This method computes the probability density function.
double	getMaxDensity() This method computes the aximum value of the probability density function.
double	getMean() This method computes the mean of the distribution, which is n r / m.
int	getPopulationSize() This method gets the population size.
int	getSampleSize() This method gets the sample size.
int	getType1Size() This method gets the number of type 1 elements.
double	getVariance() This method computes the variance, which is given by n (r/m) (1 − r/m)(m − n) / (m − 1).
void	setParameters(int m, int r, int n) This method set the parameters of the distribution and computes the domain.
void	setPopulationSize(int m) This method sets population size.
void	setSampleSize(int n) This method sets the sample size.
void	setType1Size(int r) This method sets the number of type 1 elements
double	simulate() This method simulate a value from the distribution.
java.lang.String	toString() This method returns a string that gives the name of the distribution and the values of the parameters.

Methods inherited from class edu.uah.math.distributions.Distribution

getCDF, getDomain, getFailureRate, getMedian, getMGF, getMoment, getMoment, getPGF, getQuantile, getSD, getType, setDomain, setDomain

Methods inherited from class java.lang.Object

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

Constructor Detail

HypergeometricDistribution

public HypergeometricDistribution(int m,
                                  int r,
                                  int n)

This general constructor creates a new hypergeometric distribution with specified values of the parameters.

Parameters:

m - the population size

r - the number of type 1 objects in the population

n - the sample size

HypergeometricDistribution

public HypergeometricDistribution()

This default constructor: creates a new hypergeometric distribuiton with population 100 containing 50 type 1 objects, and with sample size 10.

Method Detail

setParameters

public void setParameters(int m,
                          int r,
                          int n)

This method set the parameters of the distribution and computes the domain.

Parameters:

m - the population size

r - the number of type 1 objects

n - the sample size

getDensity

public double getDensity(double x)

This method computes the probability density function. The PDF is f(x) = C(r, x) C(m − r, n − x) / C(m, n).

Specified by:

getDensity in class Distribution

Parameters:

x - an integer between 0 and the sample size

Returns:

the probability density at x

getMaxDensity

public double getMaxDensity()

This method computes the aximum value of the probability density function. The mode occurs at (n + 1)(r + 1)/(m + 2).

Overrides:

getMaxDensity in class Distribution

Returns:

the maximum value of the probability density function

getMean

public double getMean()

This method computes the mean of the distribution, which is n r / m.

Overrides:

getMean in class Distribution

Returns:

the mean

getVariance

public double getVariance()

This method computes the variance, which is given by n (r/m) (1 − r/m)(m − n) / (m − 1).

Overrides:

getVariance in class Distribution

Returns:

the variance

setPopulationSize

public void setPopulationSize(int m)

This method sets population size.

Parameters:

m - the population size

getPopulationSize

public int getPopulationSize()

This method gets the population size.

Returns:

the population size

setType1Size

public void setType1Size(int r)

This method sets the number of type 1 elements

Parameters:

r - the number of type 1 elements

getType1Size

public int getType1Size()

This method gets the number of type 1 elements.

Returns:

the number of type 1 elements

setSampleSize

public void setSampleSize(int n)

This method sets the sample size.

Parameters:

n - the sample size

getSampleSize

public int getSampleSize()

This method gets the sample size.

Returns:

the sample size

simulate

public double simulate()

This method simulate a value from the distribution. This is done by simulating a sample of size n without replacment from the population {1, 2, ..., m} and counting the number of elemets less than r.

Overrides:

simulate in class Distribution

Returns:

a simulated value from the distribution

toString

public java.lang.String toString()

This method returns a string that gives the name of the distribution and the values of the parameters.

Overrides:

toString in class Distribution

Returns:

a string giving the name of the distribution and the values of the parameters