Package org.apache.commons.math.distribution

Class HypergeometricDistributionImpl

java.lang.Object

org.apache.commons.math.distribution.AbstractDistribution

org.apache.commons.math.distribution.AbstractIntegerDistribution

org.apache.commons.math.distribution.HypergeometricDistributionImpl

All Implemented Interfaces:

Serializable, DiscreteDistribution, Distribution, HypergeometricDistribution, IntegerDistribution

public class HypergeometricDistributionImpl
extends AbstractIntegerDistribution
implements HypergeometricDistribution, Serializable

The default implementation of HypergeometricDistribution.

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
HypergeometricDistributionImpl(int populationSize, int numberOfSuccesses, int sampleSize)	Construct a new hypergeometric distribution with the given the population size, the number of successes in the population, and the sample size.

Method Summary

Modifier and Type	Method	Description
double	cumulativeProbability(int x)	For this distribution, X, this method returns P(X ≤ x).
int	getNumberOfSuccesses()	Access the number of successes.
double	getNumericalVariance()	Returns the variance.
int	getPopulationSize()	Access the population size.
int	getSampleSize()	Access the sample size.
int	getSupportLowerBound()	Returns the lower bound for the support for the distribution.
int	getSupportUpperBound()	Returns the upper bound for the support of the distribution.
double	probability(int x)	For this distribution, X, this method returns P(X = x).
void	setNumberOfSuccesses(int num)	Deprecated. as of 2.1 (class will become immutable in 3.0)
void	setPopulationSize(int size)	Deprecated. as of 2.1 (class will become immutable in 3.0)
void	setSampleSize(int size)	Deprecated. as of 2.1 (class will become immutable in 3.0)
double	upperCumulativeProbability(int x)	For this distribution, X, this method returns P(X ≥ x).

Methods inherited from class org.apache.commons.math.distribution.AbstractIntegerDistribution

cumulativeProbability, cumulativeProbability, cumulativeProbability, inverseCumulativeProbability, isSupportLowerBoundInclusive, isSupportUpperBoundInclusive, probability, reseedRandomGenerator, sample, sample

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.apache.commons.math.distribution.DiscreteDistribution

probability

Methods inherited from interface org.apache.commons.math.distribution.Distribution

cumulativeProbability, cumulativeProbability

Methods inherited from interface org.apache.commons.math.distribution.IntegerDistribution

cumulativeProbability, inverseCumulativeProbability

Constructor Details

HypergeometricDistributionImpl

public HypergeometricDistributionImpl(int populationSize,
 int numberOfSuccesses,
 int sampleSize)

Construct a new hypergeometric distribution with the given the population size, the number of successes in the population, and the sample size.

Parameters:

populationSize - the population size.

numberOfSuccesses - number of successes in the population.

sampleSize - the sample size.

Method Details

cumulativeProbability

public double cumulativeProbability(int x)

For this distribution, X, this method returns P(X ≤ x).

Specified by:

cumulativeProbability in interface IntegerDistribution

Specified by:

cumulativeProbability in class AbstractIntegerDistribution

Parameters:

x - the value at which the PDF is evaluated.

Returns:

PDF for this distribution.

getNumberOfSuccesses

public int getNumberOfSuccesses()

Access the number of successes.

Specified by:

getNumberOfSuccesses in interface HypergeometricDistribution

Returns:

the number of successes.

getPopulationSize

public int getPopulationSize()

Access the population size.

Specified by:

getPopulationSize in interface HypergeometricDistribution

Returns:

the population size.

getSampleSize

public int getSampleSize()

Access the sample size.

Specified by:

getSampleSize in interface HypergeometricDistribution

Returns:

the sample size.

probability

public double probability(int x)

For this distribution, X, this method returns P(X = x).

Specified by:

probability in interface IntegerDistribution

Parameters:

x - the value at which the PMF is evaluated.

Returns:

PMF for this distribution.

setNumberOfSuccesses

@Deprecated
public void setNumberOfSuccesses(int num)

Deprecated.

as of 2.1 (class will become immutable in 3.0)

Modify the number of successes.

Specified by:

setNumberOfSuccesses in interface HypergeometricDistribution

Parameters:

num - the new number of successes.

Throws:

IllegalArgumentException - if num is negative.

setPopulationSize

@Deprecated
public void setPopulationSize(int size)

Deprecated.

as of 2.1 (class will become immutable in 3.0)

Modify the population size.

Specified by:

setPopulationSize in interface HypergeometricDistribution

Parameters:

size - the new population size.

Throws:

IllegalArgumentException - if size is not positive.

setSampleSize

@Deprecated
public void setSampleSize(int size)

Deprecated.

as of 2.1 (class will become immutable in 3.0)

Modify the sample size.

Specified by:

setSampleSize in interface HypergeometricDistribution

Parameters:

size - the new sample size.

Throws:

IllegalArgumentException - if size is negative.

upperCumulativeProbability

public double upperCumulativeProbability(int x)

For this distribution, X, this method returns P(X ≥ x).

Parameters:

x - the value at which the CDF is evaluated.

Returns:

upper tail CDF for this distribution.

Since:

1.1

getSupportLowerBound

public int getSupportLowerBound()

Returns the lower bound for the support for the distribution. For population size N, number of successes m, and sample size n, the lower bound of the support is max(0, n + m - N)

Returns:

lower bound of the support

Since:

2.2

getSupportUpperBound

public int getSupportUpperBound()

Returns the upper bound for the support of the distribution. For number of successes m and sample size n, the upper bound of the support is min(m, n)

Returns:

upper bound of the support

Since:

2.2

getNumericalVariance

public double getNumericalVariance()

Returns the variance. For population size N, number of successes m, and sample size n, the variance is [ n * m * (N - n) * (N - m) ] / [ N^2 * (N - 1) ]

Returns:

the variance

Since:

2.2