Class HypergeometricDistribution
java.lang.Object
org.hipparchus.distribution.discrete.AbstractIntegerDistribution
org.hipparchus.distribution.discrete.HypergeometricDistribution
 All Implemented Interfaces:
Serializable
,IntegerDistribution
Implementation of the hypergeometric distribution.

Constructor Summary
ConstructorDescriptionHypergeometricDistribution
(int populationSize, int numberOfSuccesses, int sampleSize) Construct a new hypergeometric distribution with the specified population size, number of successes in the population, and sample size. 
Method Summary
Modifier and TypeMethodDescriptiondouble
cumulativeProbability
(int x) For a random variableX
whose values are distributed according to this distribution, this method returnsP(X <= x)
.int
Access the number of successes.double
Use this method to get the numerical value of the mean of this distribution.double
Use this method to get the numerical value of the variance of this distribution.int
Access the population size.int
Access the sample size.int
Access the lower bound of the support.int
Access the upper bound of the support.boolean
Use this method to get information about whether the support is connected, i.e.double
logProbability
(int x) For a random variableX
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm.double
probability
(int x) For a random variableX
whose values are distributed according to this distribution, this method returnsP(X = x)
.double
upperCumulativeProbability
(int x) For this distribution,X
, this method returnsP(X >= x)
.Methods inherited from class org.hipparchus.distribution.discrete.AbstractIntegerDistribution
inverseCumulativeProbability, probability, solveInverseCumulativeProbability

Constructor Details

HypergeometricDistribution
public HypergeometricDistribution(int populationSize, int numberOfSuccesses, int sampleSize) throws MathIllegalArgumentException Construct a new hypergeometric distribution with the specified population size, number of successes in the population, and sample size. Parameters:
populationSize
 Population size.numberOfSuccesses
 Number of successes in the population.sampleSize
 Sample size. Throws:
MathIllegalArgumentException
 ifnumberOfSuccesses < 0
.MathIllegalArgumentException
 ifpopulationSize <= 0
.MathIllegalArgumentException
 ifnumberOfSuccesses > populationSize
, orsampleSize > populationSize
.


Method Details

cumulativeProbability
public double cumulativeProbability(int x) For a random variableX
whose values are distributed according to this distribution, this method returnsP(X <= x)
. In other words, this method represents the (cumulative) distribution function (CDF) for this distribution. Parameters:
x
 the point at which the CDF is evaluated Returns:
 the probability that a random variable with this
distribution takes a value less than or equal to
x

getNumberOfSuccesses
public int getNumberOfSuccesses()Access the number of successes. Returns:
 the number of successes.

getPopulationSize
public int getPopulationSize()Access the population size. Returns:
 the population size.

getSampleSize
public int getSampleSize()Access the sample size. Returns:
 the sample size.

probability
public double probability(int x) For a random variableX
whose values are distributed according to this distribution, this method returnsP(X = x)
. In other words, this method represents the probability mass function (PMF) for the distribution. Parameters:
x
 the point at which the PMF is evaluated Returns:
 the value of the probability mass function at
x

logProbability
public double logProbability(int x) For a random variableX
whose values are distributed according to this distribution, this method returnslog(P(X = x))
, wherelog
is the natural logarithm. In other words, this method represents the logarithm of the probability mass function (PMF) for the distribution. Note that due to the floating point precision and under/overflow issues, this method will for some distributions be more precise and faster than computing the logarithm ofIntegerDistribution.probability(int)
.The default implementation simply computes the logarithm of
probability(x)
. Specified by:
logProbability
in interfaceIntegerDistribution
 Overrides:
logProbability
in classAbstractIntegerDistribution
 Parameters:
x
 the point at which the PMF is evaluated Returns:
 the logarithm of the value of the probability mass function at
x

upperCumulativeProbability
public double upperCumulativeProbability(int x) For this distribution,X
, this method returnsP(X >= x)
. Parameters:
x
 Value at which the CDF is evaluated. Returns:
 the upper tail CDF for this distribution.

getNumericalMean
public double getNumericalMean()Use this method to get the numerical value of the mean of this distribution. For population sizeN
, number of successesm
, and sample sizen
, the mean isn * m / N
. Returns:
 the mean or
Double.NaN
if it is not defined

getNumericalVariance
public double getNumericalVariance()Use this method to get the numerical value of the variance of this distribution. For population sizeN
, number of successesm
, and sample sizen
, the variance is[n * m * (N  n) * (N  m)] / [N^2 * (N  1)]
. Returns:
 the variance (possibly
Double.POSITIVE_INFINITY
orDouble.NaN
if it is not defined)

getSupportLowerBound
public int getSupportLowerBound()Access the lower bound of the support. This method must return the same value asinverseCumulativeProbability(0)
. In other words, this method must return
For population sizeinf {x in Z  P(X <= x) > 0}
.N
, number of successesm
, and sample sizen
, the lower bound of the support ismax(0, n + m  N)
. Returns:
 lower bound of the support

getSupportUpperBound
public int getSupportUpperBound()Access the upper bound of the support. This method must return the same value asinverseCumulativeProbability(1)
. In other words, this method must return
For number of successesinf {x in R  P(X <= x) = 1}
.m
and sample sizen
, the upper bound of the support ismin(m, n)
. Returns:
 upper bound of the support

isSupportConnected
public boolean isSupportConnected()Use this method to get information about whether the support is connected, i.e. whether all integers between the lower and upper bound of the support are included in the support. The support of this distribution is connected. Returns:
true
