DiscreteSampler, SharedStateDiscreteSampler, SharedStateSampler<SharedStateDiscreteSampler>public final class KempSmallMeanPoissonSampler extends java.lang.Object implements SharedStateDiscreteSampler
This sampler is suitable for mean < 40. For large means,
LargeMeanPoissonSampler should be used instead.
Note: The algorithm uses a recurrence relation to compute the Poisson probability and a rolling summation for the cumulative probability. When the mean is large the initial probability (Math.exp(-mean)) is zero and an exception is raised by the constructor.
Sampling uses 1 call to UniformRandomProvider.nextDouble(). This method provides
an alternative to the SmallMeanPoissonSampler for slow generators of double.
| Modifier and Type | Method | Description |
|---|---|---|
static SharedStateDiscreteSampler |
of(org.apache.commons.rng.UniformRandomProvider rng,
double mean) |
Creates a new sampler for the Poisson distribution.
|
int |
sample() |
Creates a sample.
|
java.lang.String |
toString() |
|
SharedStateDiscreteSampler |
withUniformRandomProvider(org.apache.commons.rng.UniformRandomProvider rng) |
Create a new instance of the sampler with the same underlying state using the given
uniform random provider as the source of randomness.
|
public int sample()
sample in interface DiscreteSamplerpublic java.lang.String toString()
toString in class java.lang.Objectpublic SharedStateDiscreteSampler withUniformRandomProvider(org.apache.commons.rng.UniformRandomProvider rng)
withUniformRandomProvider in interface SharedStateSampler<SharedStateDiscreteSampler>rng - Generator of uniformly distributed random numbers.public static SharedStateDiscreteSampler of(org.apache.commons.rng.UniformRandomProvider rng, double mean)
rng - Generator of uniformly distributed random numbers.mean - Mean of the distribution.java.lang.IllegalArgumentException - if mean <= 0 or
Math.exp(-mean) == 0.Copyright © 2016–2019 The Apache Software Foundation. All rights reserved.