| rmsal {MixSAL} | R Documentation |
Simulate from a Mixture of Multivariate SAL Distributions
Description
Generates data from a mixture of multivariate shifted asymmetric Laplace (SAL) distributions.
Usage
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
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])