tclust (version 1.0-2)

plot.ctlcurves: Plot Method for ctlcurves Objects

Description

Plotting a ctlcurves object comparing the target functions values with different values of paramter restr.fact.

Usage

plot.ctlcurves(x, main, ylim, ylab, min.weights = FALSE, ...)

Arguments

x

The ctlcurves object to be printed.

main

A character-string containing the title of the plot.

ylim, ylab

Argument passed to plot.

min.weights

Locigal value indicating whether the minimum cluster weights shall be printed instead of the target functions values. By default this option is disabled

...

Further arguments, passed to plot.

encoding

latin1

Details

These curves show the values of the trimmed classification (log-)likelihoods when altering the trimming proportion alpha and the number of clusters k. The careful examination of these curves provides valuable information for choosing these parameters in a clustering problem. For instance, an appropriate k to be chosen is one that we do not observe a clear increase in the trimmed classification likelihood curve for k with respect to the k+1 curve for almost all the range of alpha values. Moreover, an appropriate choice of parameter alpha may be derived by determining where an initial fast increase of the trimmed classification likelihood curve stops for the final chosen k. A more detailed explanation can be found in Garc�a-Escudero et al (2009).

References

Garc�a-Escudero, L.A.; Gordaliza, A.; Matr�n, C. and Mayo-Iscar, A. (2009), "Exploring the number of groups in robust model-based clustering". Preprint available at www.eio.uva.es/infor/personas/langel.html.

Examples

sig <- diag (2)
cen <- rep (1,2)
x <- rbind (
	rmvnorm (108, cen * 0,   sig),
	rmvnorm (162, cen * 5,   sig * 6 - 2),
	rmvnorm (30, cen * 2.5, sig * 50)
)

ctl.a <- ctlcurves (x, k = 1:4, restr.fact = 12)
plot(ctl.a)