Class ZigguratSampler.Exponential

java.lang.Object

org.apache.commons.rng.sampling.distribution.ZigguratSampler

org.apache.commons.rng.sampling.distribution.ZigguratSampler.Exponential

All Implemented Interfaces:

ContinuousSampler, SharedStateContinuousSampler, SharedStateSampler<SharedStateContinuousSampler>

Enclosing class:

ZigguratSampler

public static class ZigguratSampler.Exponential
extends ZigguratSampler

Modified ziggurat method for sampling from an exponential distribution.

Since:

1.4

Nested Class Summary

Nested classes/interfaces inherited from class ZigguratSampler

ZigguratSampler.Exponential, ZigguratSampler.NormalizedGaussian

Method Summary

Modifier and Type	Method	Description
static ZigguratSampler.Exponential	of(UniformRandomProvider rng)	Create a new exponential sampler with mean = 1.
static ZigguratSampler.Exponential	of(UniformRandomProvider rng, double mean)	Create a new exponential sampler with the specified mean.
double	sample()	Creates a double sample.
String	toString()
ZigguratSampler.Exponential	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 Object

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

Methods inherited from interface ContinuousSampler

samples, samples

Method Details

toString

public String toString()

Overrides:

toString in class Object

sample

public double sample()

Creates a double sample.

Returns:

a sample.

withUniformRandomProvider

public ZigguratSampler.Exponential 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.

Parameters:

rng - Generator of uniformly distributed random numbers.

Returns:

the sampler

of

public static ZigguratSampler.Exponential of(UniformRandomProvider rng)

Create a new exponential sampler with mean = 1.

Parameters:

rng - Generator of uniformly distributed random numbers.

Returns:

the sampler

of

public static ZigguratSampler.Exponential of(UniformRandomProvider rng,
 double mean)

Create a new exponential sampler with the specified mean.

Parameters:

rng - Generator of uniformly distributed random numbers.

mean - Mean.

Returns:

the sampler

Throws:

IllegalArgumentException - if the mean is not strictly positive (mean <= 0)