fmmstDA: Discriminant analysis using Multivariate Skew t Mixture...
In EMMIXuskew: Fitting Unrestricted Multivariate Skew t Mixture Models

Description Usage Arguments Details Value references See Also Examples

performs discriminant analysis (DA) for a specified multivariate skew t mixture distribution.

1	fmmstDA(g, dat, model, tmethod=1)

`g`	a scalar specifying the number of components in the mixture model
`dat`	the data matrix giving the coordinates of the point(s) to be classified.
`model`	a list containing the parameters of the model, including `mu`, `sigma`, `delta`, `dof` (for `fmmstDA` only) and `pro`.
`tmethod`	(optional) an integer indicating which method to use when computing t distribution function values. See `pmt` for details.

For the structure of the elements of model, see dfmmst.

fmmstDA returns a vector of length nrow(dat) of the cluster labels

Lee, S. and McLachlan, G.J. (2013) EMMIXuskew: An R package for fitting mixtures of multivariate skew t-distributions via the EM algorithm. Journal of Statistical Software, 55(12), 1-22. URL http://www.jstatsoft.org/v55/i12/.

dfmmst, fmmst

obj <- list()
obj$mu <- list(c(17,19), c(5,22), c(6,10))
obj$sigma <- list(diag(2), matrix(c(2,0,0,1),2), matrix(c(3,7,7,24),2))
obj$delta <- list(c(3,1.5), c(5,10), c(2,0))
obj$dof <- c(1, 2, 3)
obj$pro <- c(0.25, 0.25, 0.5)
X2 <- rfmmst(3, 50, known=obj)
fmmstDA(3, X2[,1:2], obj)