Compute quick cluster analysis

## Not run: 
##D # k-means clustering of mtcars-dataset
##D sjc.qclus(mtcars)
##D 
##D # k-means clustering of mtcars-dataset with 4 pre-defined
##D # groups in a faceted panel
##D sjc.qclus(airquality,
##D           groupcount = 4,
##D           facetCluster = TRUE)
## End(Not run)

# k-means clustering of airquality data
# and saving the results. most likely, 3 cluster
# groups have been found (see below).
airgrp <- sjc.qclus(airquality)

## Clustering Gap statistic ["clusGap"].
## B=100 simulated reference sets, k = 1..10
## 
##  --> Number of clusters (method 'Tibs2001SEmax', SE.factor=1): 3

plot of chunk sjc.qclus

# "re-plot" cluster groups, without computing
# new k-means cluster analysis.
sjc.qclus(airquality,
          groupcount = 3,
          groups = airgrp$classification)

plot of chunk sjc.qclus