plot.clustEff {clustEff}

Plot Clustering Effects

Description

Produces a dendrogram, a cluster plot and a boxplot of average distance cluster of an object of class “clustEff”.

Usage

## S3 method for class 'clustEff'
plot(x, xvar=c("clusters", "dendrogram", "boxplot", "numclust"), which,
        polygon=TRUE, dissimilarity=TRUE, par=FALSE, ...)

Arguments

x

An object of class “clustEdd”, typically the result of a call to clustEff.

xvar

Clusters: plot of the k clusters; Dendrogram: plot of the tree after computing the dissimilarity measure and applying a hierarchical clustering algorithm; Boxplot: plot the average distance within clusters; Numclust: plot the curve to minimize to select the best number of clusters;

which

If missing all curves effect are plotted.

polygon

If TRUE confidence intervals are represented by shaded areas via polygon. Otherwise, dashed lines are used. If NULL no confidence intervals are represented

dissimilarity

If TRUE dissimilarity measure within each cluster is used to do boxplot representation.

par

If TRUE the screen is automaticcaly splitted.

...

additional graphical parameters, that can include xlim, ylim, xlab, ylab, col, lwd, lty. See par.

Details

Different plot for the clustering algorithm.

Author(s)

Gianluca Sottile [e-mail]

See Also

clustEff for cluster algorithm; extract.object for extracting information through a quantile regression coefficient modeling in a multivariate case; summary.clustEff for clustering summary.

Examples

  # using simulated data

  # see the documentation for 'clustEff'