Class RejectionInversionZipfSampler

java.lang.Object

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

org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSampler

All Implemented Interfaces:

DiscreteSampler, SharedStateDiscreteSampler, SharedStateSampler<SharedStateDiscreteSampler>

public class RejectionInversionZipfSampler
extends SamplerBase
implements SharedStateDiscreteSampler

Implementation of the Zipf distribution.

Sampling uses UniformRandomProvider.nextDouble().

Since:

1.0

Constructor Summary

Constructors

Constructor	Description
RejectionInversionZipfSampler(UniformRandomProvider rng, int numberOfElements, double exponent)	This instance delegates sampling.

Method Summary

Modifier and Type	Method	Description
static SharedStateDiscreteSampler	of(UniformRandomProvider rng, int numberOfElements, double exponent)	Creates a new Zipf distribution sampler.
int	sample()	Rejection inversion sampling method for a discrete, bounded Zipf distribution that is based on the method described in Wolfgang Hörmann and Gerhard Derflinger.
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.

Methods inherited from class SamplerBase

nextDouble, nextInt, nextInt, nextLong

Methods inherited from class Object

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

Methods inherited from interface DiscreteSampler

samples, samples

Constructor Details

RejectionInversionZipfSampler

public RejectionInversionZipfSampler(UniformRandomProvider rng,
 int numberOfElements,
 double exponent)

This instance delegates sampling. Use the factory method of(UniformRandomProvider, int, double) to create an optimal sampler.

Parameters:

rng - Generator of uniformly distributed random numbers.

numberOfElements - Number of elements.

exponent - Exponent.

Throws:

IllegalArgumentException - if numberOfElements <= 0 or exponent < 0.

Method Details

sample

public int sample()

Rejection inversion sampling method for a discrete, bounded Zipf distribution that is based on the method described in

Wolfgang Hörmann and Gerhard Derflinger. "Rejection-inversion to generate variates from monotone discrete distributions",
ACM Transactions on Modeling and Computer Simulation (TOMACS) 6.3 (1996): 169-184.

Specified by:

sample in interface DiscreteSampler

Returns:

a sample.

toString

public String toString()

Overrides:

toString in class SamplerBase

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:

withUniformRandomProvider in interface SharedStateSampler<SharedStateDiscreteSampler>

Parameters:

rng - Generator of uniformly distributed random numbers.

Returns:

the sampler

Since:

1.3

of

public static SharedStateDiscreteSampler of(UniformRandomProvider rng,
 int numberOfElements,
 double exponent)

Creates a new Zipf distribution sampler.

Note when exponent = 0 the Zipf distribution reduces to a discrete uniform distribution over the interval [1, n] with n the number of elements.

Parameters:

rng - Generator of uniformly distributed random numbers.

numberOfElements - Number of elements.

exponent - Exponent.

Returns:

the sampler

Throws:

IllegalArgumentException - if numberOfElements <= 0 or exponent < 0.

Since:

1.3