public class PoissonSampler extends SamplerBase implements SharedStateDiscreteSampler
Knuth (1969). Seminumerical Algorithms. The Art of Computer Programming, Volume 2. Chapter 3.4.1.F.3 Important integer-valued distributions: The Poisson distribution. Addison Wesley.The Poisson process (and hence, the returned value) is bounded by
1000 * mean
.
Devroye, Luc. (1981). The Computer Generation of Poisson Random Variables
Computing vol. 26 pp. 197-207.
Sampling uses:
UniformRandomProvider.nextDouble()
UniformRandomProvider.nextLong()
(large means only)
Constructor and Description |
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PoissonSampler(UniformRandomProvider rng,
double mean)
This instance delegates sampling.
|
Modifier and Type | Method and Description |
---|---|
static SharedStateDiscreteSampler |
of(UniformRandomProvider rng,
double mean)
Creates a new Poisson distribution sampler.
|
int |
sample()
Creates an
int sample. |
String |
toString() |
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.
|
nextDouble, nextInt, nextInt, nextLong
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
samples, samples
public PoissonSampler(UniformRandomProvider rng, double mean)
of(UniformRandomProvider, double)
to create an optimal sampler.rng
- Generator of uniformly distributed random numbers.mean
- Mean.IllegalArgumentException
- if mean <= 0
or mean > 0.5 *
Integer.MAX_VALUE
.public int sample()
int
sample.sample
in interface DiscreteSampler
public String toString()
toString
in class SamplerBase
public SharedStateDiscreteSampler withUniformRandomProvider(UniformRandomProvider rng)
withUniformRandomProvider
in interface SharedStateSampler<SharedStateDiscreteSampler>
rng
- Generator of uniformly distributed random numbers.public static SharedStateDiscreteSampler of(UniformRandomProvider rng, double mean)
rng
- Generator of uniformly distributed random numbers.mean
- Mean.IllegalArgumentException
- if mean <= 0
or mean > 0.5 *
Integer.MAX_VALUE
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