Last data update: 2014.03.03

 R: groupals
groupalsR Documentation

groupals

Description

Implements a constrained homogeneity analysis to take into account the cluster structure of objects as described in Van Buuren and Heiser (1989).

Usage

groupals(data,nclus,ndim,nstart=100,smartStart=F,seed=1234)

Arguments

data

categorical dataset

nclus

number of clusters

ndim

dimensionality of the solution

nstart

number of random starts

smartStart

If TRUE then starting values are obtained with fuzzy c-means

seed

seed is used to set the random number seed when smartStart = FALSE

Value

obscoord

object scores

attcoord

attribute scores

centroid

cluster centroids

cluID

cluster membership

criterion

optimal value of the objective function

Author(s)

Markos, A. amarkos@gmail.com, Iodice D'Enza, A. iodicede@gmail.com and Van de Velden, M. vandevelden@ese.eur.nl

References

Van Buuren, S. and Heiser, W. J. (1989). Clustering n objects in k groups under optimal scaling of variables, Psychometrika, 54, 699-706.

See Also

MCAk, fuzzyMCAk, iFCB

Examples

     data(underwear)
     attlab = c(c(1:15),"by","tr","vm","jd","ml","bn","bg","ck","a1","a2","a3")
     outgroupals <- groupals(underwear,nclus=3,ndim=2,nstart=1,smartStart=TRUE,seed=1234)
     plotrd(outgroupals,attlabel=attlab)

Results


Created & Maintained by Osamu Ogasawara (osamu.ogasawara@gmail.com) and IMSBIO