mclust/
mclass
mreloc(classification, x, method = "S*", signif = rep(0, ncol(x)),
noise = F, scale = rep(1,ncol(x)),
shape = c( 1, rep(.2, (ncol(x)-1))), workspace = 10*nrow(x),
iterations = nrow(x))
mclass, or else an integer vector giving the classification
for each data point (e.g., the classification component of the output from
mclass).
mclust:
"S*",
"S",
"spherical"
(with varying sizes),
"sum of squares" or
"trace"
(Ward's method),
"unconstrained", and
"determinant".
Only enough of the string to determine a unique match is required.
The default is
"S*".
x.
Nonpositive components are allowed. This is used in initializing clustering
in some methods.
ith column of
x is multiplied by
scale[i] before cluster analysis.
The default is
rep(1, ncol(x)).
"S*" and
"S".
The default is
c(1, rep( .2, (ncol(x)-1))).
Although all options are allowed,
method
,
noise,
error,
scale, and
shape would
usually be expected to be the same as the input to
mclust.
years <- c("1960", "1964", "1968", "1972", "1976")
votes.clust <- mclust(votes.repub[,years], method = "S", noise = T)
# plot the awe on the current graphics device
plot(x = 1:length(votes.clust$awe), y = votes.clust$awe)
votes.class <- mclass(votes.clust, 3)
votes.reloc <- mreloc(votes.class, votes.repub[,years], method = "S",
noise = T)