org.apache.commons.math.distribution
Interface IntegerDistribution

All Superinterfaces:

DiscreteDistribution, Distribution

All Known Subinterfaces:

BinomialDistribution, HypergeometricDistribution, PascalDistribution, PoissonDistribution, ZipfDistribution

All Known Implementing Classes:

AbstractIntegerDistribution, BinomialDistributionImpl, HypergeometricDistributionImpl, PascalDistributionImpl, PoissonDistributionImpl, ZipfDistributionImpl

public interface IntegerDistribution
extends DiscreteDistribution

Interface for discrete distributions of integer-valued random variables.

Version:

$Id: IntegerDistribution.java 1178295 2011-10-03 04:36:27Z psteitz $

Method Summary

double	cumulativeProbability(int x) For a random variable X whose values are distributed according to this distribution, this method returns P(X <= x).
double	cumulativeProbability(int x0, int x1) For this distribution, X, this method returns P(x0 <= X <= x1).
int	inverseCumulativeProbability(double p) For this distribution, X, this method returns the largest x such that P(X <= x) <= p.
double	probability(int x) For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
void	reseedRandomGenerator(long seed) Reseed the random generator used to generate samples.
int	sample() Generate a random value sampled from this distribution.
int[]	sample(int sampleSize) Generate a random sample from the distribution.

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

probability

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

cumulativeProbability, cumulativeProbability, getNumericalMean, getNumericalVariance, isSupportConnected, isSupportLowerBoundInclusive, isSupportUpperBoundInclusive

Method Detail

probability

double probability(int x)

For a random variable 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 for the distribution.

Parameters:

x - Value at which the probability density function is evaluated.

Returns:

the value of the probability density function at x.

cumulativeProbability

double cumulativeProbability(int x)

For a random variable X whose values are distributed according to this distribution, this method returns P(X <= x). In other words, this method represents the probability distribution function, or PDF for the distribution.

Parameters:

x - Value at which the PDF is evaluated.

Returns:

PDF for this distribution.

cumulativeProbability

double cumulativeProbability(int x0,
                             int x1)

For this distribution, X, this method returns P(x0 <= X <= x1).

Parameters:

x0 - the inclusive, lower bound

x1 - the inclusive, upper bound

Returns:

the cumulative probability.

Throws:

java.lang.IllegalArgumentException - if x0 > x1.

inverseCumulativeProbability

int inverseCumulativeProbability(double p)

For this distribution, X, this method returns the largest x such that P(X <= x) <= p.
Note that this definition implies:

• If there is a minimum value, m, with positive probability under (the density of) X, then m - 1 is returned by inverseCumulativeProbability(0). If there is no such value m, Integer.MIN_VALUE is returned.
• If there is a maximum value, M, such that P(X <= M) = 1, then M is returned by inverseCumulativeProbability(1). If there is no such value, M, Integer.MAX_VALUE is returned.

Parameters:

p - Cumulative probability.

Returns:

the largest x such that P(X < x) <= p.

Throws:

java.lang.IllegalArgumentException - if p is not between 0 and 1 (inclusive).

reseedRandomGenerator

void reseedRandomGenerator(long seed)

Reseed the random generator used to generate samples.

Parameters:

seed - New seed.

Since:

3.0

sample

int sample()

Generate a random value sampled from this distribution.

Returns:

a random value.

Since:

3.0

sample

int[] sample(int sampleSize)

Generate a random sample from the distribution.

Parameters:

sampleSize - number of random values to generate.

Returns:

an array representing the random sample.

Throws:

NotStrictlyPositiveException - if sampleSize is not positive.

Since:

3.0