mstepE( data, z, prior=NULL, warn=NULL, ...)
mstepV( data, z, prior=NULL, warn=NULL, ...)
mstepEII( data, z, prior=NULL, warn=NULL, ...)
mstepVII( data, z, prior=NULL, warn=NULL, ...)
mstepEEI( data, z, prior=NULL, warn=NULL, ...)
mstepVEI( data, z, prior=NULL, warn=NULL, control=NULL, ...)
mstepEVI( data, z, prior=NULL, warn=NULL, ...)
mstepVVI( data, z, prior=NULL, warn=NULL, ...)
mstepEEE( data, z, prior=NULL, warn=NULL, ...)
mstepEEV( data, z, prior=NULL, warn=NULL, ...)
mstepVEV( data, z, prior=NULL, warn=NULL, control=NULL,...)
mstepVVV( data, z, prior=NULL, warn=NULL, ...)
[i,k]
th entry is the
conditional probability of the ith observation belonging to
the kth component of the mixture.
In analyses involving noise, this should not include the
conditional probabilities fo.Mclust$warn
."VEI"
and "VEV"
that have an iterative M-step. This should be a list with components
named itmax and tol. These components can be of length 1
or 2; in the ldo.call
.mstep
,
me
,
estep
,
priorControl
emControl
mstepVII(data = iris[,-5], z = unmap(iris[,5]))
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