bootFlexclust {flexclust}R Documentation

Bootstrap Flexclust Algorithms

Description

Runs clustering algorithms repeatedly for different numbers of clusters on bootstrap replica of the original data and returns corresponding cluster assignments, centroids and Rand indices comparing pairs of partitions.

Usage

bootFlexclust(x, k, nboot=100, correct=TRUE, seed=NULL,
              multicore=TRUE, verbose=FALSE, ...)

## S4 method for signature 'bootFlexclust':
summary(object)
## S4 method for signature 'bootFlexclust, missing':
plot(x, y, ...)
## S4 method for signature 'bootFlexclust':
boxplot(x, ...)
## S4 method for signature 'bootFlexclust':
densityplot(x, data, ...)

Arguments

x, k, ... Passed to stepFlexclust.
nboot Number of bootstrap pairs of partitions.
correct Logical, correct the index for agreement by chance?
seed If not NULL, a call to set.seed() is made before any clustering is done.
multicore If TRUE, use package multicore for parallel processing if available. Availability of multicore is checked when flexclust is loaded and stored in getOption("flexclust")$have_multicore. Set to FALSE for debugging and more sensible error messages in case something goes wrong.
verbose If TRUE, show progress information during computations. Ignored if multicore=TRUE.
y, data Not used.
object An object of class "bootFlexclust".

Author(s)

Friedrich Leisch

See Also

stepFlexclust

Examples

## data uniform on unit square
x <- matrix(runif(400), ncol=2)

bcl <- bootFlexclust(x, k=2:7, nboot=20, FUN=cclust)

bcl
summary(bcl)

## splitting the square into four quadrants should be the most stable
## solution (increase nboot if not)
plot(bcl)
densityplot(bcl, from=0)

[Package flexclust version 1.2-2 Index]