ddmst: The Multivariate Skew t-distribution
In EMMIXskew: The EM Algorithm and Skew Mixture Distribution

Description Usage Arguments Value See Also Examples

Density and random generation for Multivariate Skew t-distributions with mean vector mean, covariance matrix cov, degrees of freedom nu, and skew parameter verctor del.

1 2	ddmst(dat,n, p, mean, cov, nu, del) rdmst( n, p, mean, cov, nu, del)

`dat`	An n by p numeric matrix, the dataset
`n`	An integer, the number of observations
`p`	An integer, the dimension of data
`mean`	A length of p vector, the mean
`cov`	A p by p matrix, the covariance
`nu`	A positive number, the degrees of freedom
`del`	A length of p vector, the skew parameter

ddmst gives the density values; rdmst generates the random numbers

rdemmix,ddmvn,ddmvt, ddmsn,rdmvn,rdmvt, rdmsn.

n <- 100
p <- 2

mean <- rep(0,p)
cov  <- diag(p)
nu <- 3
del <- c(0,1)

set.seed(3214)

y   <- rdmst(  n,p,mean,cov,nu,del)

den <- ddmst(y,n,p,mean,cov,nu,del)