mstepE(data, z, equalPro, noise = FALSE, ...)
mstepV(data, z, equalPro, noise = FALSE, ...)
mstepEII(data, z, equalPro, noise = FALSE, ...)
mstepVII(data, z, equalPro, noise = FALSE, ...)
mstepEEI(data, z, equalPro, noise = FALSE, eps, warnSingular, ...)
mstepVEI(data, z, equalPro, noise = FALSE, eps, tol, itmax, warnSingular, ...)
mstepEVI(data, z, equalPro, noise = FALSE, eps, warnSingular, ...)
mstepVVI(data, z, equalPro, noise = FALSE, eps, warnSingular, ...)
mstepEEE(data, z, equalPro, noise = FALSE, ...)
mstepEEV(data, z, equalPro, noise = FALSE, eps, warnSingular, ...)
mstepVVV(data, z, equalPro, noise = FALSE, ...)
[i,k]
th entry is the
conditional probability of the ith observation belonging to
the kth component of the mixture..Mclust$equalPro
.eps
allows computations to
proceed nearer to singularity.
The default is .Mclust$eps
.Mclust$tol
..Mclust$itmax
..Mclust$warnSingular
.
Not used for models "EII", "VII", "EEE", "VVV".do.call
.[,,k]
th entry gives the
the covariance for the kth group in the best model. [i,k]
th entry is the
conditional probability of the ith observation belonging to
the kth component of the mixture."info"
Information on the iteration.
"warn"
An appropriate warning if problems are
encountered in the computations.mstep
,
me
,
estep
,
mclustOptions
mstepVII(data = irisMatrix, z = unmap(irisClass))