org.apache.commons.rng.sampling.distribution

Class PoissonSampler

java.lang.Object

org.apache.commons.rng.sampling.distribution.SamplerBase

org.apache.commons.rng.sampling.distribution.PoissonSampler

All Implemented Interfaces:

DiscreteSampler

public class PoissonSampler
extends SamplerBase
implements DiscreteSampler

Sampler for the Poisson distribution.

• For small means, a Poisson process is simulated using uniform deviates, as described here. The Poisson process (and hence, the returned value) is bounded by 1000 * mean.
• For large means, we use the rejection algorithm described in

  Devroye, Luc. (1981).The Computer Generation of Poisson Random Variables
  Computing vol. 26 pp. 197-207.

Constructor Summary

Constructors

Constructor and Description
PoissonSampler(UniformRandomProvider rng, double mean)

Method Summary

Modifier and Type	Method and Description
int	sample() Creates a sample.
String	toString()

Methods inherited from class org.apache.commons.rng.sampling.distribution.SamplerBase

nextDouble, nextInt, nextInt

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

PoissonSampler

public PoissonSampler(UniformRandomProvider rng,
                      double mean)

Parameters:

rng - Generator of uniformly distributed random numbers.

mean - Mean.

Throws:

IllegalArgumentException - if mean <= 0.

Method Detail

sample

public int sample()

Creates a sample.

Specified by:

sample in interface DiscreteSampler

Returns:

a sample.

toString

public String toString()

Overrides:

toString in class SamplerBase