Random Samples From a Power Exponential Distributions

Description

Function to obtain random samples from a multivariate power exponential distribution.

Usage

rmvpowerexp(n, Location = rep(0, nrow(Scatter)), 
            Scatter = diag(length(Location)), Beta = 1)

Arguments

Details

The power exponential distribution is an elliptical distribution which can have light or heavy tails. Beta = 1 yields a multivariate normal distribution, Beta = 0.5 the multivariate Laplace distribution and with increasing Beta converges to a multivariate uniform distribution.

Value

a matrix.

Author(s)

Klaus Nordhausen

References

Oja, H. (2010), Multivariate Nonparametric Methods with R, Springer.

See Also

rmvnorm, rmvt

Examples

X1 <- rmvpowerexp(100,c(0,0,0),Beta = 0.5)
pairs(X1)
X2 <- rmvpowerexp(100,c(0,0,0),Beta = 1)
pairs(X2)
X3 <- rmvpowerexp(100,c(0,0,0),Beta = 10)
pairs(X3)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(MNM)
Loading required package: ICSNP
Loading required package: mvtnorm
Loading required package: ICS
Loading required package: SpatialNP
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MNM/rmvpowerexp.Rd_%03d_medium.png", width=480, height=480)
> ### Name: rmvpowerexp
> ### Title: Random Samples From a Power Exponential Distributions
> ### Aliases: rmvpowerexp
> ### Keywords: distribution multivariate
> 
> ### ** Examples
> 
> X1 <- rmvpowerexp(100,c(0,0,0),Beta = 0.5)
> pairs(X1)
> X2 <- rmvpowerexp(100,c(0,0,0),Beta = 1)
> pairs(X2)
> X3 <- rmvpowerexp(100,c(0,0,0),Beta = 10)
> pairs(X3)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>