org.apache.commons.math.distribution
Class HypergeometricDistributionImpl

java.lang.Object
  extended by org.apache.commons.math.distribution.AbstractDistribution
      extended by org.apache.commons.math.distribution.AbstractIntegerDistribution
          extended by 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.

Version:
$Revision: 1054524 $ $Date: 2011-01-03 05:59:18 +0100 (lun. 03 janv. 2011) $
See Also:
Serialized Form

Field Summary
 
Fields inherited from class org.apache.commons.math.distribution.AbstractIntegerDistribution
randomData
 
Constructor Summary
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
 double cumulativeProbability(int x)
          For this distribution, X, this method returns P(X ≤ x).
protected  int getDomainLowerBound(double p)
          Access the domain value lower bound, based on p, used to bracket a PDF root.
protected  int getDomainUpperBound(double p)
          Access the domain value upper bound, based on p, used to bracket a PDF root.
 int getNumberOfSuccesses()
          Access the number of successes.
protected  double getNumericalMean()
          Returns the mean.
 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
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 
Methods inherited from interface org.apache.commons.math.distribution.IntegerDistribution
cumulativeProbability, inverseCumulativeProbability
 
Methods inherited from interface org.apache.commons.math.distribution.DiscreteDistribution
probability
 
Methods inherited from interface org.apache.commons.math.distribution.Distribution
cumulativeProbability, cumulativeProbability
 

Constructor Detail

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 Detail

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.

getDomainLowerBound

protected int getDomainLowerBound(double p)
Access the domain value lower bound, based on p, used to bracket a PDF root.

Specified by:
getDomainLowerBound in class AbstractIntegerDistribution
Parameters:
p - the desired probability for the critical value
Returns:
domain value lower bound, i.e. P(X < lower bound) < p

getDomainUpperBound

protected int getDomainUpperBound(double p)
Access the domain value upper bound, based on p, used to bracket a PDF root.

Specified by:
getDomainUpperBound in class AbstractIntegerDistribution
Parameters:
p - the desired probability for the critical value
Returns:
domain value upper bound, i.e. P(X < upper bound) > p

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

getNumericalMean

protected double getNumericalMean()
Returns the mean. For population size N, number of successes m, and sample size n, the mean is n * m / N

Returns:
the mean
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


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