meE(data, z, eps, tol, itmax, equalPro, warnSingular,
noise = FALSE, Vinv)
meV(data, z, eps, tol, itmax, equalPro, warnSingular,
noise = FALSE, Vinv)
meEII(data, z, eps, tol, itmax, equalPro, warnSingular,
noise = FALSE, Vinv)
meVII(data, z, eps, tol, itmax, equalPro, warnSingular,
noise = FALSE, Vinv)
meEEI(data, z, eps, tol, itmax, equalPro, warnSingular,
noise = FALSE, Vinv)
meVEI(data, z, eps, tol, itmax, equalPro, warnSingular,
noise = FALSE, Vinv)
meEVI(data, z, eps, tol, itmax, equalPro, warnSingular,
noise = FALSE, Vinv)
meVVI(data, z, eps, tol, itmax, equalPro, warnSingular,
noise = FALSE, Vinv)
meEEE(data, z, eps, tol, itmax, equalPro, warnSingular,
noise = FALSE, Vinv)
meEEV(data, z, eps, tol, itmax, equalPro, warnSingular,
noise = FALSE, Vinv)
meVEV(data, z, eps, tol, itmax, equalPro, warnSingular,
noise = FALSE, Vinv)
meVVV(data, z, eps, tol, itmax, equalPro, warnSingular,
noise = FALSE, Vinv)
[i,k]
th entry is the
conditional probability of the ith observation belonging to
the kth component of the mixture.eps
allows computations to
proceed nearer to singularity.
The default is .Mclust$eps
.Mclust$tol
..Mclust$itmax
..Mclust$equalPro
..Mclust$warnSingular
.hypvol
to the data.
Used only when noise = TRUE
.[,,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.em
,
me
,
estep
,
mclustOptions
meVVV(data = irisMatrix, z = unmap(irisClass))