KempSmallMeanPoissonSampler (Apache Commons RNG Sampling 1.5 API)

java.lang.Object
- org.apache.commons.rng.sampling.distribution.KempSmallMeanPoissonSampler

All Implemented Interfaces:

DiscreteSampler, SharedStateDiscreteSampler, SharedStateSampler<SharedStateDiscreteSampler>
```
public final class KempSmallMeanPoissonSampler
extends Object
implements SharedStateDiscreteSampler
```
Sampler for the Poisson distribution.
- Kemp, A, W, (1981) Efficient Generation of Logarithmically Distributed Pseudo-Random Variables. Journal of the Royal Statistical Society. Vol. 30, No. 3, pp. 249-253.
This sampler is suitable for mean < 40. For large means, LargeMeanPoissonSampler should be used instead.

Note: The algorithm uses a recurrence relation to compute the Poisson probability and a rolling summation for the cumulative probability. When the mean is large the initial probability (Math.exp(-mean)) is zero and an exception is raised by the constructor.

Sampling uses 1 call to UniformRandomProvider.nextDouble(). This method provides an alternative to the SmallMeanPoissonSampler for slow generators of double.
Since:

1.3

See Also:

Kemp, A.W. (1981) JRSS Vol. 30, pp. 249-253

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`static SharedStateDiscreteSampler`	`of(UniformRandomProvider rng, double mean)`	Creates a new sampler for the Poisson distribution.
`int`	`sample()`	Creates an `int` sample.
`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 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

- Method Detail
  - sample
```
public int sample()
```
    Creates an int sample.
    
    Specified by:
    
    sample in interface DiscreteSampler
    
    Returns:
    
    a sample.
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object
  - 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
  - of
```
public static SharedStateDiscreteSampler of(UniformRandomProvider rng,
                                            double mean)
```
    Creates a new sampler for the Poisson distribution.
    
    Parameters:
    
    rng - Generator of uniformly distributed random numbers.
    
    mean - Mean of the distribution.
    
    Returns:
    
    the sampler
    
    Throws:
    
    IllegalArgumentException - if mean <= 0 or Math.exp(-mean) == 0.