shipunov (version 1.5)

Jclust: Simple bootstrap and jackknife clustering

Description

Simple bootstrap and jackknife clustering

Usage

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, ...)

Arguments

data

Data

n.cl

Number of desired clusters

iter

Number of iterations

method.d

Distance method

method.c

Hierarchical clustering method

bootstrap

Bootstrap or jackknife?

x

Object of the class 'Jclust'

rect.lty

Line type for the rectangles

rect.col

Color of rectangles

main

Plot title

xlab

Horizontal axis label

sub

Horizontal axis sub-label

...

Additional arguments to the 'print()' or 'plot.hclust()'

Value

Returns 'Jclust' object.

Details

Simple method to bootstrap and jackknife cluster memberships, and plot consensus membership tree. Requires the desired number of clusters.

See Also

Bclust, BootA

Examples

# 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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