Package org.apache.commons.rng.sampling.distribution

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

nextDouble, nextInt, nextInt, nextLong

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

Constructor Detail

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 Detail

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