# rStable: Generate Data From Stable Distributions In portes: Portmanteau Tests for Univariate and Multivariate Time Series Models

## Description

Generate data from stable distribution with infinite variance.

## Usage

 1  rStable(n, Alpha, Beta, Scale = NULL, Location = NULL) 

## Arguments

 n length of the series. Alpha index stability parameters, each in the range (0,2]. Beta skewness parameters, each in the range [-1, 1]. Scale scale parameters. Location location parameters.

## Details

Alpha, Beta, Scale, and Location should have the same length. This length, k, represents the number of the variables that we need to generate. The code in the function rStable extends that one given in the package fBasics to the multivariate case. Many thanks to Diethelm Wuertz for putting his code under the GPL license.

## Value

A vector of dimension n\times k from independent stable distributions.

## Author(s)

Esam Mahdi and A.I. McLeod.

## References

Chambers, J.M., Mallows, C.L., and Stuck, B.W. (1976). "A Method for Simulating Stable Random Variables". Journal of American Statistical Association, 71, 340-344.

Wuertz, D., core team members R (2014). "fBasics: Rmetrics - Markets and Basic Statistics". R package version 3011.87. https://CRAN.R-project.org/package=fBasics

There is also a function rstable in the fBasics package for the univariate case only. See also fitstable, varima.sim

## Examples

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 ## Generate Univariate Data n <- 500 Alpha <- 1.75 Beta <- 0 Scale <- 1.5 Location <- 0 rStable(n, Alpha, Beta, Scale, Location) ## Generate Bivariate Data n <- 500 Alpha <- c(1.3,1.5) Beta <- c(0.3,-0.6) rStable(n, Alpha, Beta) ## Generate Multivariate Data n <- 500 Alpha <- c(1.3,1.5,1.7) Beta <- c(0.3,-0.6,0) Scale <- c(3,1,6) rStable(n, Alpha, Beta,Scale) 

portes documentation built on Jan. 13, 2021, 6:28 p.m.