Class KempSmallMeanPoissonSampler
- java.lang.Object
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- org.apache.commons.rng.sampling.distribution.KempSmallMeanPoissonSampler
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- All Implemented Interfaces:
DiscreteSampler,SharedStateDiscreteSampler,SharedStateSampler<SharedStateDiscreteSampler>
public final class KempSmallMeanPoissonSampler extends Object implements SharedStateDiscreteSampler
Sampler for the Poisson distribution.- Kemp, A, W, (1981) Efficient Generation of Logarithmically Distributed Pseudo-Random Variables. Journal of the Royal Statistical Society. Vol. 30, No. 3, pp. 249-253.
This sampler is suitable for
mean < 40. For large means,LargeMeanPoissonSamplershould 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 theSmallMeanPoissonSamplerfor slow generators ofdouble.- Since:
- 1.3
- See Also:
- Kemp, A.W. (1981) JRSS Vol. 30, pp. 249-253
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static SharedStateDiscreteSamplerof(UniformRandomProvider rng, double mean)Creates a new sampler for the Poisson distribution.intsample()Creates anintsample.StringtoString()SharedStateDiscreteSamplerwithUniformRandomProvider(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.-
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
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Methods inherited from interface org.apache.commons.rng.sampling.distribution.DiscreteSampler
samples, samples
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Method Detail
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sample
public int sample()
Creates anintsample.- Specified by:
samplein interfaceDiscreteSampler- Returns:
- a sample.
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withUniformRandomProvider
public SharedStateDiscreteSampler withUniformRandomProvider(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.- Specified by:
withUniformRandomProviderin interfaceSharedStateSampler<SharedStateDiscreteSampler>- Parameters:
rng- Generator of uniformly distributed random numbers.- Returns:
- the sampler
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of
public static SharedStateDiscreteSampler of(UniformRandomProvider rng, double mean)
Creates a new sampler for the Poisson distribution.- Parameters:
rng- Generator of uniformly distributed random numbers.mean- Mean of the distribution.- Returns:
- the sampler
- Throws:
IllegalArgumentException- ifmean <= 0orMath.exp(-mean) == 0.
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