Displaying 1 result from an estimated 1 matches for "clusterrange".
2010 Jan 06
1
positive log likelihood and BIC values from mCLUST analysis
...ce = FALSE, plot = FALSE,
old.wa = FALSE)
######################### BEGIN EM ANALYSIS #########################
#Use the points determined by MDS to perform EM clustering.
#Allow only the unconstrained models. Sometimes, constrained models mess
things up!
EMclusters <- mclustBIC(mds$points, G=Clusterrange, modelNames= c("VII",
"VVI", "VVV"), prior=NULL, control=emControl(),
initialization=list(hcPairs=NULL, subset=NULL, noise=NULL),
Vinv=NULL, warn=FALSE, x=NULL)
The input data are in the form of an N X N matrix of pairwise genetic
distances betwe...