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.
i
th 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)