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

Description

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`.

Usage

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

Arguments

 `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

Value

`ddmst` gives the density values; `rdmst` generates the random numbers

`rdemmix`,`ddmvn`,`ddmvt`, `ddmsn`,`rdmvn`,`rdmvt`, `rdmsn`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```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) ```