Poisson

java.lang.Object

org.drip.sequence.random.UnivariateSequenceGenerator

org.drip.sequence.random.Poisson

public class Poisson
extends UnivariateSequenceGenerator

Poisson implements the Poisson Random Number Generator.

Module = Numerical Core Module
Library = Statistical Learning Library
Project = Sequence
Package = Random

Author:: Lakshmi Krishnamurthy

Constructor Summary

Constructors

Constructor Description

Poisson(double dblLambda)
Construct a Poisson Random Number Generator

Method Summary

Modifier and Type	Method	Description
`double`	`lambda()`	Retrieve Lambda
`double`	`random()`	Generate a Random Number according to the specified rule
`SingleSequenceAgnosticMetrics`	`sequence(int iNumEntry, R1Univariate distPopulation)`	Generate a Random Sequence along with its Metrics

Methods inherited from class org.drip.sequence.random.UnivariateSequenceGenerator

sequence

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details
- Poisson
  
  public Poisson(double dblLambda) throws java.lang.Exception
  
  Construct a Poisson Random Number Generator
  
  Parameters:
  
  dblLambda - Lambda
  
  Throws:
  
  java.lang.Exception - Thrown if the inputs are invalid
Method Details
- lambda
  
  public double lambda()
  
  Retrieve Lambda
  
  Returns:
  
  Lambda
- random
  
  public double random()
  
  Description copied from class: UnivariateSequenceGenerator
  
  Generate a Random Number according to the specified rule
  
  Specified by:
  
  random in class UnivariateSequenceGenerator
  
  Returns:
  
  The Random Number
- sequence
  
  public SingleSequenceAgnosticMetrics sequence(int iNumEntry, R1Univariate distPopulation)
  
  Description copied from class: UnivariateSequenceGenerator
  
  Generate a Random Sequence along with its Metrics
  
  Overrides:
  
  sequence in class UnivariateSequenceGenerator
  
  Parameters:
  
  iNumEntry - Number of Entries in the Sequence
  
  distPopulation - The True Underlying Generator Distribution of the Population
  
  Returns:
  
  The Random Sequence (along with its Metrics)