statistic.distribution
Class ChapeauSigmaDistribution

java.lang.Object
  |
  +--statistic.distribution.GenericDistribution
        |
        +--statistic.distribution.GenericDiscreteDistribution
              |
              +--statistic.distribution.ChapeauSigmaDistribution
All Implemented Interfaces:
RandomGenerator

public class ChapeauSigmaDistribution
extends GenericDiscreteDistribution


Field Summary
 SigmaDistribution sd
          loi de chapeausigma :
P(chapeausigma=k) = P(sigma>=k)/E(sigma) = P(sigma(0,j)=k) for k>=1
where E is mean
 
Fields inherited from class statistic.distribution.GenericDiscreteDistribution
cdf
 
Fields inherited from class statistic.distribution.GenericDistribution
name, paramNames, params
 
Fields inherited from interface statistic.RandomGenerator
random
 
Constructor Summary
ChapeauSigmaDistribution(SigmaDistribution sigmaDistribution)
          ChapeauSigmaDistribution
ChapeauSigmaDistribution(SigmaDistribution sigmaDistribution, boolean cdf)
          ChapeauSigmaDistribution
 
Method Summary
 double cdf(int k)
          Method cdf.
 double getFMAX()
          Method getFMAX: For some Discrete Distribution we could have a pb to generate a randInt because of the cdf value So when we generate random value we verify that this value is < getFMAX()
 double getSumCdf(int k)
           
 void initializeSumCdf(int a, int b)
           
static void main(java.lang.String[] args)
          Methode: Main pour tester la classe
 double mean()
          Method mean.
 double var()
          Returns the variance of the distribution
 
Methods inherited from class statistic.distribution.GenericDiscreteDistribution
cdf, getInitialisationStatus, getKMAX, pdf, rand, randInt, randIntFast, setInitialisationStatus
 
Methods inherited from class statistic.distribution.GenericDistribution
getEquation, getName, getParam, getParamName, getParams, getParamsCount, getParamsNames, normalStandardCdf, setParam, setParams
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

sd

public SigmaDistribution sd
loi de chapeausigma :
P(chapeausigma=k) = P(sigma>=k)/E(sigma) = P(sigma(0,j)=k) for k>=1
where E is mean

Constructor Detail

ChapeauSigmaDistribution

public ChapeauSigmaDistribution(SigmaDistribution sigmaDistribution)
ChapeauSigmaDistribution


ChapeauSigmaDistribution

public ChapeauSigmaDistribution(SigmaDistribution sigmaDistribution,
                                boolean cdf)
ChapeauSigmaDistribution

Method Detail

cdf

public double cdf(int k)
           throws java.lang.IllegalArgumentException
Method cdf. chapeauSigmacdf(k) = P(chapeauSigma=k) = P(sigma>=k)/E(sigma) = 1/ E(sigma) *[1-sum(sigmacdf(l),1,k-1)]

Specified by:
cdf in class GenericDiscreteDistribution
Parameters:
k -
Returns:
double
Throws:
java.lang.IllegalArgumentException
See Also:
statistic.GenericDiscreteDistribution#cdf(int)

initializeSumCdf

public void initializeSumCdf(int a,
                             int b)

getSumCdf

public double getSumCdf(int k)
                 throws java.lang.IllegalArgumentException
Specified by:
getSumCdf in class GenericDiscreteDistribution
java.lang.IllegalArgumentException

getFMAX

public double getFMAX()
Description copied from class: GenericDiscreteDistribution
Method getFMAX: For some Discrete Distribution we could have a pb to generate a randInt because of the cdf value So when we generate random value we verify that this value is < getFMAX()

Overrides:
getFMAX in class GenericDiscreteDistribution
Returns:
double

mean

public double mean()
Method mean. E(ChapeauSigma) = sum(ro(k),0,inf) = 1/2( 1 +E(sigma^2)/E(sigma) )

Specified by:
mean in class GenericDistribution
Returns:
double the mean value
See Also:
statistic.GenericDistribution#mean()

var

public double var()
Description copied from class: GenericDistribution
Returns the variance of the distribution

Specified by:
var in class GenericDistribution

main

public static void main(java.lang.String[] args)
Methode: Main pour tester la classe