ddmsn: The Multivariate Skew Normal Distribution

In EMMIXskew: The EM Algorithm and Skew Mixture Distribution

Description

Density and random generation for Multivariate Skew Normal distributions with mean vector mean, covariance matrix cov, and skew parameter vector del.

Usage

ddmsn(dat,n, p, mean, cov, del)
rdmsn(    n, p, mean, cov, 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
del	A length of p vector, the skew parameter

Value

ddmsn gives the density values; rdmsn generates the random numbers

See Also

rdemmix,ddmvn,ddmvt, ddmst,rdmvn,rdmvt, rdmst.

Examples

n <- 100
p <- 2

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

set.seed(3214)

y   <- rdmsn(  n,p,mean,cov,del)

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

EMMIXskew documentation built on May 2, 2019, 11:07 a.m.