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java.lang.Objectorg.apache.commons.math3.distribution.AbstractIntegerDistribution
org.apache.commons.math3.distribution.HypergeometricDistribution
public class HypergeometricDistribution
Implementation of the hypergeometric distribution.
Field Summary |
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Fields inherited from class org.apache.commons.math3.distribution.AbstractIntegerDistribution |
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random, randomData |
Constructor Summary | |
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HypergeometricDistribution(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. |
|
HypergeometricDistribution(RandomGenerator rng,
int populationSize,
int numberOfSuccesses,
int sampleSize)
Creates a new hypergeometric distribution. |
Method Summary | |
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protected double |
calculateNumericalVariance()
Used by getNumericalVariance() . |
double |
cumulativeProbability(int x)
For a random variable X whose values are distributed according
to this distribution, this method returns P(X <= x) . |
int |
getNumberOfSuccesses()
Access the number of successes. |
double |
getNumericalMean()
Use this method to get the numerical value of the mean of this distribution. |
double |
getNumericalVariance()
Use this method to get the numerical value of the variance of this distribution. |
int |
getPopulationSize()
Access the population size. |
int |
getSampleSize()
Access the sample size. |
int |
getSupportLowerBound()
Access the lower bound of the support. |
int |
getSupportUpperBound()
Access the upper bound of the support. |
boolean |
isSupportConnected()
Use this method to get information about whether the support is connected, i.e. |
double |
probability(int x)
For a random variable X whose values are distributed according
to this distribution, this method returns P(X = x) . |
double |
upperCumulativeProbability(int x)
For this distribution, X , this method returns P(X >= x) . |
Methods inherited from class org.apache.commons.math3.distribution.AbstractIntegerDistribution |
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cumulativeProbability, inverseCumulativeProbability, reseedRandomGenerator, sample, sample, solveInverseCumulativeProbability |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public HypergeometricDistribution(int populationSize, int numberOfSuccesses, int sampleSize) throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException
populationSize
- Population size.numberOfSuccesses
- Number of successes in the population.sampleSize
- Sample size.
NotPositiveException
- if numberOfSuccesses < 0
.
NotStrictlyPositiveException
- if populationSize <= 0
.
NumberIsTooLargeException
- if numberOfSuccesses > populationSize
,
or sampleSize > populationSize
.public HypergeometricDistribution(RandomGenerator rng, int populationSize, int numberOfSuccesses, int sampleSize) throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException
rng
- Random number generator.populationSize
- Population size.numberOfSuccesses
- Number of successes in the population.sampleSize
- Sample size.
NotPositiveException
- if numberOfSuccesses < 0
.
NotStrictlyPositiveException
- if populationSize <= 0
.
NumberIsTooLargeException
- if numberOfSuccesses > populationSize
,
or sampleSize > populationSize
.Method Detail |
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public double cumulativeProbability(int x)
X
whose values are distributed according
to this distribution, this method returns P(X <= x)
. In other
words, this method represents the (cumulative) distribution function
(CDF) for this distribution.
x
- the point at which the CDF is evaluated
x
public int getNumberOfSuccesses()
public int getPopulationSize()
public int getSampleSize()
public double probability(int x)
X
whose values are distributed according
to this distribution, this method returns P(X = x)
. In other
words, this method represents the probability mass function (PMF)
for the distribution.
x
- the point at which the PMF is evaluated
x
public double upperCumulativeProbability(int x)
X
, this method returns P(X >= x)
.
x
- Value at which the CDF is evaluated.
public double getNumericalMean()
N
, number of successes m
, and sample
size n
, the mean is n * m / N
.
Double.NaN
if it is not definedpublic double getNumericalVariance()
N
, number of successes m
, and sample
size n
, the variance is
[n * m * (N - n) * (N - m)] / [N^2 * (N - 1)]
.
Double.POSITIVE_INFINITY
or
Double.NaN
if it is not defined)protected double calculateNumericalVariance()
getNumericalVariance()
.
public int getSupportLowerBound()
inverseCumulativeProbability(0)
. In other words, this
method must return
inf {x in Z | P(X <= x) > 0}
.
N
, number of successes m
, and sample
size n
, the lower bound of the support is
max(0, n + m - N)
.
public int getSupportUpperBound()
inverseCumulativeProbability(1)
. In other words, this
method must return
inf {x in R | P(X <= x) = 1}
.
m
and sample size n
, the upper
bound of the support is min(m, n)
.
public boolean isSupportConnected()
true
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