Class ZigguratSampler.Exponential
- java.lang.Object
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- org.apache.commons.rng.sampling.distribution.ZigguratSampler
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- org.apache.commons.rng.sampling.distribution.ZigguratSampler.Exponential
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- 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 distributions.
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Nested Class Summary
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Nested classes/interfaces inherited from class org.apache.commons.rng.sampling.distribution.ZigguratSampler
ZigguratSampler.Exponential, ZigguratSampler.NormalizedGaussian
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static ZigguratSampler.Exponentialof(UniformRandomProvider rng)Create a new exponential sampler withmean = 1.static ZigguratSampler.Exponentialof(UniformRandomProvider rng, double mean)Create a new exponential sampler with the specifiedmean.doublesample()Creates a sample.StringtoString()ZigguratSampler.ExponentialwithUniformRandomProvider(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.
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Method Detail
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sample
public double sample()
Creates a sample.- Returns:
- a sample.
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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
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of
public static ZigguratSampler.Exponential of(UniformRandomProvider rng)
Create a new exponential sampler withmean = 1.- Parameters:
rng- Generator of uniformly distributed random numbers.- Returns:
- the sampler
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of
public static ZigguratSampler.Exponential of(UniformRandomProvider rng, double mean)
Create a new exponential sampler with the specifiedmean.- Parameters:
rng- Generator of uniformly distributed random numbers.mean- Mean.- Returns:
- the sampler
- Throws:
IllegalArgumentException- if the mean is not strictly positive (mean <= 0)
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