Class MarsagliaTsangWangDiscreteSampler.Binomial.MarsagliaTsangWangFixedResultBinomialSampler
java.lang.Object
org.apache.commons.rng.sampling.distribution.MarsagliaTsangWangDiscreteSampler.AbstractMarsagliaTsangWangDiscreteSampler
org.apache.commons.rng.sampling.distribution.MarsagliaTsangWangDiscreteSampler.Binomial.MarsagliaTsangWangFixedResultBinomialSampler
- All Implemented Interfaces:
DiscreteSampler
,SharedStateDiscreteSampler
,SharedStateSampler<SharedStateDiscreteSampler>
- Enclosing class:
MarsagliaTsangWangDiscreteSampler.Binomial
private static final class MarsagliaTsangWangDiscreteSampler.Binomial.MarsagliaTsangWangFixedResultBinomialSampler
extends MarsagliaTsangWangDiscreteSampler.AbstractMarsagliaTsangWangDiscreteSampler
Return a fixed result for the Binomial distribution. This is a special class to handle
an edge case of probability of success equal to 0 or 1.
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Field Summary
FieldsFields inherited from class org.apache.commons.rng.sampling.distribution.MarsagliaTsangWangDiscreteSampler.AbstractMarsagliaTsangWangDiscreteSampler
rng
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Constructor Summary
Constructors -
Method Summary
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
Methods inherited from interface org.apache.commons.rng.sampling.distribution.DiscreteSampler
samples, samples
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Field Details
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result
private final int resultThe result.
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Constructor Details
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MarsagliaTsangWangFixedResultBinomialSampler
MarsagliaTsangWangFixedResultBinomialSampler(int result) - Parameters:
result
- Result.
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Method Details
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sample
public int sample()Description copied from interface:DiscreteSampler
Creates anint
sample.- Returns:
- a sample.
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toString
Description copied from class:MarsagliaTsangWangDiscreteSampler.AbstractMarsagliaTsangWangDiscreteSampler
- Overrides:
toString
in classMarsagliaTsangWangDiscreteSampler.AbstractMarsagliaTsangWangDiscreteSampler
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withUniformRandomProvider
Description copied from interface:SharedStateSampler
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.- Parameters:
rng
- Generator of uniformly distributed random numbers.- Returns:
- the sampler
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