Simple bootstrap and jackknife clustering
Jclust(data, n.cl, iter=100, method.d="manhattan", method.c="ward.D", bootstrap=TRUE)
# S3 method for Jclust
print(x, ...)
# S3 method for Jclust
plot(x, main="", xlab="", sub=NULL, rect.lty=3, rect.col=1, ...)
Data
Number of desired clusters
Number of iterations
Distance method
Hierarchical clustering method
Bootstrap or jackknife?
Object of the class 'Jclust'
Line type for the rectangles
Color of rectangles
Plot title
Horizontal axis label
Horizontal axis sub-label
Additional arguments to the 'print()' or 'plot.hclust()'
Simple bootstrap and jackknife clustering, requires the desired number of clusters.
Alternative: 'pvc::pvc()'.
Bclust
, link{BootA}
# NOT RUN {
(mo.j <- Jclust(t(moldino), 3, iter=1000))
plot(mo.j)
# }
# NOT RUN {
## This is how one can bootstrap _all_ reliable cluster numbers:
for (i in 2:(nrow(t(moldino)) - 1)) print(Jclust(t(moldino), i, iter=1000, boot=TRUE))
# }
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