# rmsal: Simulate from a Mixture of Multivariate SAL Distributions In MixSAL: Mixtures of Multivariate Shifted Asymmetric Laplace (SAL) Distributions

## Description

Generates data from a mixture of multivariate shifted asymmetric Laplace (SAL) distributions.

## Usage

 `1` ```rmsal(n, p, alpha, sig, mu, pi.g) ```

## Arguments

 `n` The number of observations required. `p` The dimension of the data. `alpha` A matrix where each row specifies the direction of skewness in each variable for each mixture component. `sig` An array where each matrix specifies the covariance matrix for each mixture component. `mu` A matrix where each row gives the mean vector for each mixture component. `pi.g` A vector specifying the mixing components.

## Value

An n by p + 1 matrix where each row corresponds to one observation from the specified mixture of SAL distributions. The first column gives the component (or group) label for each observation and columns 2 to p + 1 give the values of the p-dimensional observation.

## Author(s)

Brian C. Franczak [aut, cre], Ryan P. Browne [aut, ctb], Paul D. McNicholas [aut, ctb]

Maintainer: Brian C. Franczak <franczakb@macewan.ca>

## References

Franczak et. al (2014). Mixtures of Shifted Asymmetric Laplace Distributions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(6), 1149-1157.

## Examples

 ```1 2 3 4 5 6 7 8``` ```alpha <- matrix(c(2,2,1,2),2,2) sig <- array(NA,dim=c(2,2,2)) sig[,,1] <- diag(2) sig[,,2] <- matrix(c(1,0.5,0.5,1),2,2) mu <- matrix(c(0,0,-2,5),2,2) pi.g <- rep(1/2,2) x <- rmsal(n=500,p=2,alpha=alpha,sig=sig,mu=mu,pi.g=pi.g) plot(x[,-1],col=x[,1],pch=x[,1]) ```

MixSAL documentation built on May 2, 2019, 7:04 a.m.