Package 'fpc' - open source solution for an Internet free, intelligent ...

26 cluster.varstats
clusterwise
logical. If FALSE, only the output tables are computed but no more detail and
graphs are given on the fly.
tablevar vector of integers. Numbers of variables treated as categorical (i.e., no histograms
and statistics, just tables) if clusterwise=TRUE. Note that an error will
be produced by factor type variables unless they are declared as categorical here.
catvar
quantvar
catvarcats
proportions
projmethod
minsize
ask
rangefactor
x
Value
digits
... not used.
vector of integers. Numbers of variables to be categorised by proportional quantiles
for table computation. Recommended for all continuous variables.
vector of integers. Variables for which means, standard deviations and quantiles
should be given out if clusterwise=TRUE.
integer. Number of categories used for categorisation of variables specified in
quantvar.
logical. If TRUE, output tables contain proportions, otherwise numbers of observations.
one of "none", "dc", "bc", "vbc", "mvdc", "adc", "awc" (recommended if
not "none"), "arc", "nc", "wnc", "anc". Cluster validation projection method
introduced in Hennig (2004), passed on as method argument in discrproj.
integer. Projection is not carried out for clusters with fewer points than this. (If
this is chosen smaller, it may lead to errors with some projection methods.)
logical. If TRUE, par(ask=TRUE) is set in the beginning to prompt the user
before plots and par(ask=FALSE) in the end.
numeric. Factor by which to multiply the range for projection plot ranges.
an object of class "varwisetables", output object of cluster.varstats.
integer. Number of digits after the decimal point to print out.
An object of class "varwisetables", which is a list with a table for each variable, giving (categorised)
marginal distributions by cluster.
Author(s)
Christian Hennig http://www.homepages.ucl.ac.uk/~ucakche
References
Hennig, C. (2004) Asymmetric linear dimension reduction for classification. Journal of Computational
and Graphical Statistics 13, 930-945 .
Examples
set.seed(112233)
data(Cars93)
Cars934