SSJ API Documentation
Stochastic Simulation in Java
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umontreal.ssj.randvar.Pearson5Gen Class Reference

THIS CLASS HAS BEEN RENAMED InverseGammaGen . More...

Inheritance diagram for umontreal.ssj.randvar.Pearson5Gen:
umontreal.ssj.randvar.RandomVariateGen

Public Member Functions

 Pearson5Gen (RandomStream s, double alpha, double beta)
 THIS CLASS HAS BEEN RENAMED InverseGammaGen .
 Pearson5Gen (RandomStream s, double alpha)
 Creates a Pearson5 random variate generator with parameters.
 Pearson5Gen (RandomStream s, Pearson5Dist dist)
 Creates a new generator for the distribution dist, using stream s.
double getAlpha ()
 Returns the parameter \(\alpha\) of this object.
double getBeta ()
 Returns the parameter \(\beta\) of this object.
Public Member Functions inherited from umontreal.ssj.randvar.RandomVariateGen
 RandomVariateGen (RandomStream s, Distribution dist)
 Creates a new random variate generator from the distribution dist, using stream s.
double nextDouble ()
 Generates a random number from the continuous distribution contained in this object.
void nextArrayOfDouble (double[] v, int start, int n)
 Generates n random numbers from the continuous distribution contained in this object.
double[] nextArrayOfDouble (int n)
 Generates n random numbers from the continuous distribution contained in this object, and returns them in a new array of size n.
RandomStream getStream ()
 Returns the umontreal.ssj.rng.RandomStream used by this generator.
void setStream (RandomStream stream)
 Sets the umontreal.ssj.rng.RandomStream used by this generator to stream.
Distribution getDistribution ()
 Returns the umontreal.ssj.probdist.Distribution used by this generator.
String toString ()
 Returns a String containing information about the current generator.

Static Public Member Functions

static double nextDouble (RandomStream s, double alpha, double beta)
 Generates a variate from the Pearson V distribution with shape parameter \(\alpha> 0\) and scale parameter \(\beta> 0\).

Detailed Description

THIS CLASS HAS BEEN RENAMED InverseGammaGen .

This class implements random variate generators for the Pearson type V distribution with shape parameter \(\alpha> 0\) and scale parameter

\(\beta> 0\). The density function of this distribution is

\[ f(x) = \left\{\begin{array}{ll} \displaystyle\frac{x^{-(\alpha+ 1)}e^{-\beta/ x}}{\beta^{-\alpha} \Gamma(\alpha)} & \quad\mbox{for } x > 0 \\ 0 & \quad\mbox{otherwise,} \end{array} \right. \tag{fpearson5} \]

where \(\Gamma\) is the gamma function.

Definition at line 48 of file Pearson5Gen.java.

Constructor & Destructor Documentation

◆ Pearson5Gen() [1/3]

umontreal.ssj.randvar.Pearson5Gen.Pearson5Gen ( RandomStream s,
double alpha,
double beta )

THIS CLASS HAS BEEN RENAMED InverseGammaGen .

Creates a Pearson5 random variate generator with parameters

\(\alpha=\) alpha and \(\beta=\) beta, using stream s.

Definition at line 58 of file Pearson5Gen.java.

◆ Pearson5Gen() [2/3]

umontreal.ssj.randvar.Pearson5Gen.Pearson5Gen ( RandomStream s,
double alpha )

Creates a Pearson5 random variate generator with parameters.

\(\alpha=\) alpha and \(\beta= 1\), using stream s.

Definition at line 68 of file Pearson5Gen.java.

◆ Pearson5Gen() [3/3]

umontreal.ssj.randvar.Pearson5Gen.Pearson5Gen ( RandomStream s,
Pearson5Dist dist )

Creates a new generator for the distribution dist, using stream s.

Definition at line 75 of file Pearson5Gen.java.

Member Function Documentation

◆ getAlpha()

double umontreal.ssj.randvar.Pearson5Gen.getAlpha ( )

Returns the parameter \(\alpha\) of this object.

Definition at line 92 of file Pearson5Gen.java.

◆ getBeta()

double umontreal.ssj.randvar.Pearson5Gen.getBeta ( )

Returns the parameter \(\beta\) of this object.

Definition at line 99 of file Pearson5Gen.java.

◆ nextDouble()

double umontreal.ssj.randvar.Pearson5Gen.nextDouble ( RandomStream s,
double alpha,
double beta )
static

Generates a variate from the Pearson V distribution with shape parameter \(\alpha> 0\) and scale parameter \(\beta> 0\).

Definition at line 85 of file Pearson5Gen.java.


The documentation for this class was generated from the following file: