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

Class InverseTransformParetoSampler

java.lang.Object

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

org.apache.commons.rng.sampling.distribution.InverseTransformParetoSampler

All Implemented Interfaces:

ContinuousSampler, SharedStateContinuousSampler, SharedStateSampler<SharedStateContinuousSampler>

public class InverseTransformParetoSampler
extends SamplerBase
implements SharedStateContinuousSampler

Sampling from a Pareto distribution.

Sampling uses UniformRandomProvider.nextLong().

Since:

1.0

Field Summary

Fields

Modifier and Type	Field	Description
private final LongToDoubleFunction	nextDouble	Method to generate the (1 - p) value.
private final double	oneOverShape	1 / Shape.
private final UniformRandomProvider	rng	Underlying source of randomness.
private final double	scale	Scale.

Constructor Summary

Constructors

Modifier	Constructor	Description
private	InverseTransformParetoSampler(double scale, double shape, UniformRandomProvider rng)
	InverseTransformParetoSampler(UniformRandomProvider rng, double scale, double shape)	Create an instance.
private	InverseTransformParetoSampler(UniformRandomProvider rng, InverseTransformParetoSampler source)

Method Summary

Modifier and Type	Method	Description
static SharedStateContinuousSampler	of(UniformRandomProvider rng, double scale, double shape)	Creates a new Pareto distribution sampler.
double	sample()	Creates a double sample.
String	toString()
SharedStateContinuousSampler	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.ContinuousSampler

samples, samples

Field Details

scale

private final double scale

Scale.

oneOverShape

private final double oneOverShape

1 / Shape.

rng

private final UniformRandomProvider rng

Underlying source of randomness.

nextDouble

private final LongToDoubleFunction nextDouble

Method to generate the (1 - p) value.

Constructor Details

InverseTransformParetoSampler

public InverseTransformParetoSampler(UniformRandomProvider rng,
 double scale,
 double shape)

Create an instance.

Parameters:

rng - Generator of uniformly distributed random numbers.

scale - Scale of the distribution.

shape - Shape of the distribution.

Throws:

IllegalArgumentException - if scale <= 0 or shape <= 0

InverseTransformParetoSampler

private InverseTransformParetoSampler(double scale,
 double shape,
 UniformRandomProvider rng)

Parameters:

scale - Scale of the distribution.

shape - Shape of the distribution.

rng - Generator of uniformly distributed random numbers.

InverseTransformParetoSampler

private InverseTransformParetoSampler(UniformRandomProvider rng,
 InverseTransformParetoSampler source)

Parameters:

rng - Generator of uniformly distributed random numbers.

source - Source to copy.

Method Details

sample

public double sample()

Creates a double sample.

Specified by:

sample in interface ContinuousSampler

Returns:

a sample.

toString

public String toString()

Overrides:

toString in class SamplerBase

withUniformRandomProvider

public SharedStateContinuousSampler 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<SharedStateContinuousSampler>

Parameters:

rng - Generator of uniformly distributed random numbers.

Returns:

the sampler

Since:

1.3

of

public static SharedStateContinuousSampler of(UniformRandomProvider rng,
 double scale,
 double shape)

Creates a new Pareto distribution sampler.

Parameters:

rng - Generator of uniformly distributed random numbers.

scale - Scale of the distribution.

shape - Shape of the distribution.

Returns:

the sampler

Throws:

IllegalArgumentException - if scale <= 0 or shape <= 0

Since:

1.3