estepE(data, mu, sigmasq, pro, eps, warnSingular, Vinv, ...)
estepV(data, mu, sigmasq, pro, eps, warnSingular, Vinv, ...)
estepEII(data, mu, sigmasq, pro, eps, warnSingular, Vinv, ...)
estepVII(data, mu, sigmasq, pro, eps, warnSingular, Vinv, ...)
estepEEI(data, mu, decomp, pro, eps, warnSingular, Vinv, ...)
estepVEI(data, mu, decomp, pro, eps, warnSingular, Vinv, ...)
estepEVI(data, mu, decomp, pro, eps, warnSingular, Vinv, ...)
estepVVI(data, mu, decomp, pro, eps, warnSingular, Vinv, ...)
estepEEE(data, mu, Sigma, pro, eps, warnSingular, Vinv, ...)
estepEEV(data, mu, decomp, pro, eps, warnSingular, Vinv, ...)
estepVEV(data, mu, decomp, pro, eps, warnSingular, Vinv, ...)
estepVVV(data, mu, sigma, pro, eps, warnSingular, Vinv, ...)
mu
is a matrix whose columns are the
means of the components.cdens
.[,,k]
th entry is the covariance matrix for the kth
component of the mixture model.eps
allow computations to proceed nearer to singularity. The
default is .Mclust$eps
..Mclust$warnSingular
.hypvol
to the
data. Used only when pro
includes an additional mixing
proportion for a noise component.decomp
, sigma
or cholsigma
for model "VVV",
decomp
for models "VII" and "EII", and Sigma
or
cholSigma
for mod[i,k]
th entry is the
conditional probability of the ith observation belonging to
the kth component of the mixture."warn"
: An appropriate warning if problems are
encountered in the computations.do.call
, allowing the output of e.g. mstep
to be passed
without the need to specify individual parameters as arguments.estep
,
em
,
mstep
,
do.call
,
mclustOptions
data(iris)
irisMatrix <- as.matrix(iris[,1:4])
irisClass <- iris[,5]
msEst <- mstepEII(data = irisMatrix, z = unmap(irisClass))
names(msEst)
estepEII(data = irisMatrix, mu = msEst$mu, pro = msEst$pro,
sigmasq = msEst$sigmasq)
do.call("estepEII", c(list(data=irisMatrix), msEst)) ## alternative call
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