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2010 Jan 06
1
positive log likelihood and BIC values from mCLUST analysis
...MDS to perform EM clustering.
#Allow only the unconstrained models. Sometimes, constrained models mess
things up!
EMclusters <- mclustBIC(mds$points, G=Clusterrange, modelNames= c("VII",
"VVI", "VVV"), prior=NULL, control=emControl(),
initialization=list(hcPairs=NULL, subset=NULL, noise=NULL),
Vinv=NULL, warn=FALSE, x=NULL)
The input data are in the form of an N X N matrix of pairwise genetic
distances between strains. Those distances can either be the total
number of differences over X characters, or can be normalized to the
fraction
of char...
2010 Apr 19
1
What is mclust up to? Different clusters found if x and y interchanged
Hello All...
I gave a task to my students that involved using mclust to look for clusters
in some bivariate data of isotopes vs various mining locations. They
discovered something I didn?t expect; the data (called tur) is appended
below.
p <- qplot(x = dD, y = dCu65, data = tur, color = mine)
print(p) # simple bivariate plot of the data; looks fine
mod1 <- Mclust(tur[,2:3])
mod1$G
mod2