ml_clust {lazy.cluster} | R Documentation |
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.
ml_clust(x, ncl = 2, maxiter = 50, eps = 1e-06, nstart = 0, method = 1, init_method = "ward.D2", print = 0)
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 |
method |
= 1 to use mxnormal, = 2 to use EMCluster::emcluster |
init_method |
method for clust |
print |
= 1 or 2 to print some result |
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.
A class "emret" object to which
betweenss, totss, tot.withinss
are added.
resml <- ml_clust( circle2, 5, print=2 )