MVN {EMCluster}  R Documentation 
These functions are tools for compute density of (mixture) multivariate Gaussian distribution with unstructured dispersion.
dmvn(x, mu, LTsigma, log = FALSE)
dlmvn(x, mu, LTsigma, log = TRUE)
dmixmvn(x, emobj = NULL, pi = NULL, Mu = NULL, LTSigma = NULL, log = FALSE)
logL(x, emobj = NULL, pi = NULL, Mu = NULL, LTSigma = NULL)
x 
the data matrix, dimension 
mu 
the centers of clusters, length 
LTsigma 
the lower triangular matrices of dispersion, length

log 
if logarithm returned. 
emobj 
the desired model which is a list mainly contains 
pi 
the mixing proportion, length 
Mu 
the centers of clusters, dimension 
LTSigma 
the lower triangular matrices of dispersion,

The dmvn
and dlmvn
compute density and log density of
multivariate distribution.
The dmixmvn
computes density of mixture multivariate distribution
and is based either an input emobj
or inputs pi
,
Mu
, and LTSigma
to assign class id to each observation of
x
.
The logL
returns the value of the observed log likelihood function
of the parameters at the current values of the parameters pi
,
Mu
, and LTSigma
, with the suplied data matrix x
.
A density value is returned.
WeiChen Chen wccsnow@gmail.com and Ranjan Maitra.
https://www.stat.iastate.edu/people/ranjanmaitra
library(EMCluster, quietly = TRUE)
x2 < da2$da
x3 < da3$da
emobj2 < list(pi = da2$pi, Mu = da2$Mu, LTSigma = da2$LTSigma)
emobj3 < list(pi = da3$pi, Mu = da3$Mu, LTSigma = da3$LTSigma)
logL(x2, emobj = emobj2)
logL(x3, emobj = emobj3)
dmixmvn2 < dmixmvn(x2, emobj2)
dmixmvn3 < dmixmvn(x3, emobj3)
dlmvn(da2$da[1,], da2$Mu[1,], da2$LTSigma[1,])
log(dmvn(da2$da[1,], da2$Mu[1,], da2$LTSigma[1,]))