Class AhrensDieterExponentialSampler
java.lang.Object
org.apache.commons.rng.sampling.distribution.SamplerBase
org.apache.commons.rng.sampling.distribution.AhrensDieterExponentialSampler
- All Implemented Interfaces:
ContinuousSampler,SharedStateContinuousSampler,SharedStateSampler<SharedStateContinuousSampler>
public class AhrensDieterExponentialSampler
extends SamplerBase
implements SharedStateContinuousSampler
Sampling from an exponential distribution.
Sampling uses:
- Since:
- 1.0
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Field Summary
FieldsModifier and TypeFieldDescriptionprivate static final double[]Table containing the constants \( q_i = sum_{j=1}^i (\ln 2)^j / j! = \ln 2 + (\ln 2)^2 / 2 + ...private final doubleThe mean of this distribution.private final UniformRandomProviderUnderlying source of randomness. -
Constructor Summary
ConstructorsModifierConstructorDescriptionprivateAhrensDieterExponentialSampler(double mean, UniformRandomProvider rng) AhrensDieterExponentialSampler(UniformRandomProvider rng, double mean) Create an instance. -
Method Summary
Modifier and TypeMethodDescriptionstatic SharedStateContinuousSamplerof(UniformRandomProvider rng, double mean) Create a new exponential distribution sampler.doublesample()Creates adoublesample.toString()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, nextLongMethods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface org.apache.commons.rng.sampling.distribution.ContinuousSampler
samples, samples
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Field Details
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EXPONENTIAL_SA_QI
private static final double[] EXPONENTIAL_SA_QITable containing the constants \( q_i = sum_{j=1}^i (\ln 2)^j / j! = \ln 2 + (\ln 2)^2 / 2 + ... + (\ln 2)^i / i! \) until the largest representable fraction below 1 is exceeded. Note that \( 1 = 2 - 1 = \exp(\ln 2) - 1 = sum_{n=1}^\infinity (\ln 2)^n / n! \) thus \( q_i \rightarrow 1 as i \rightarrow +\infinity \), so the higher \( i \), the closer we get to 1 (the series is not alternating). By trying, n = 16 in Java is enough to reach 1. -
mean
private final double meanThe mean of this distribution. -
rng
Underlying source of randomness.
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Constructor Details
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AhrensDieterExponentialSampler
Create an instance.- Parameters:
rng- Generator of uniformly distributed random numbers.mean- Mean of this distribution.- Throws:
IllegalArgumentException- ifmean <= 0
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AhrensDieterExponentialSampler
- Parameters:
mean- Mean.rng- Generator of uniformly distributed random numbers.
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Method Details
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sample
public double sample()Creates adoublesample.- Specified by:
samplein interfaceContinuousSampler- Returns:
- a sample.
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toString
- Overrides:
toStringin classSamplerBase
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withUniformRandomProvider
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:
withUniformRandomProviderin interfaceSharedStateSampler<SharedStateContinuousSampler>- Parameters:
rng- Generator of uniformly distributed random numbers.- Returns:
- the sampler
- Since:
- 1.3
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of
Create a new exponential distribution sampler.- Parameters:
rng- Generator of uniformly distributed random numbers.mean- Mean of the distribution.- Returns:
- the sampler
- Throws:
IllegalArgumentException- ifmean <= 0- Since:
- 1.3
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