SmallMeanPoissonSampler (VirtualDataSet API)

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

All Implemented Interfaces:

DiscreteSampler
```
public class SmallMeanPoissonSampler
extends java.lang.Object
implements DiscreteSampler
```
Sampler for the Poisson distribution.
- For small means, a Poisson process is simulated using uniform deviates, as described here. The Poisson process (and hence, the returned value) is bounded by 1000 * mean.
This sampler is suitable for mean < 40. For large means, LargeMeanPoissonSampler should be used instead.

Sampling uses UniformRandomProvider.nextDouble().
Since:

1.1

- Constructor Summary
  
  Constructors
  Constructor Description
  
  SmallMeanPoissonSampler(UniformRandomProvider rng, double mean)
- Method Summary
  
  Modifier and Type Method Description
  
  int sample()
  Creates a sample.
  
  java.lang.String toString()
  - Methods inherited from class java.lang.Object
    clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - SmallMeanPoissonSampler
```
public SmallMeanPoissonSampler(UniformRandomProvider rng,
                               double mean)
```
    Parameters:
    
    rng - Generator of uniformly distributed random numbers.
    
    mean - Mean.
    
    Throws:
    
    java.lang.IllegalArgumentException - if mean <= 0 or Math.exp(-mean) is not positive.
- Method Detail
  - sample
```
public int sample()
```
    Creates a sample.
    
    Specified by:
    
    sample in interface DiscreteSampler
    
    Returns:
    
    a sample.
  - toString
```
public java.lang.String toString()
```
    Overrides:
    
    toString in class java.lang.Object