ml_clust {lazy.cluster}

R Documentation

Normal Mixture Clustering

Description

This function uses mxnormal function to perform Maximum Likelihood cluster analysis under multivariate normal model.
The main purpose of this function is to be used from "dhclust" function.

Usage

ml_clust(x, ncl = 2, maxiter = 50, eps = 1e-06, nstart = 0,
  method = 1, init_method = "ward.D2", print = 0)

Arguments

x	obs x variable data frame
ncl	# of clusters to be sought
maxiter	max # of iterations
eps	criterion for convergence of ML
nstart	= 0 to use hclust solution as the initial = n to use n random initail by kmeans to find the best solution
method	= 1 to use mxnormal, = 2 to use EMCluster::emcluster (method = 2 deleted.)
init_method	method for clust
print	= 1 or 2 to print some result

Details

This version returns the ML cluster result only if
nrow(x) > 2*ncl
where 2 stands for the minimum obs to calculate variance.
Otherwise, LS solution will be sought by stat::kmeans function.

Value

A class "emret" object to which
betweenss, totss, tot.withinss
are added.

Examples

resml <- ml_clust( circle2, 5, print=2 )

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