bootockc: Bootstrap Order Constrained k-means Clustering

In ockc: Order Constrained Solutions in k-Means Clustering

Bootstrap Order Constrained k-means Clustering

Description

Runs ockc for different numbers of clusters on bootstrap replica of the original data (maintaining the supplied order) and returns corresponding cluster assignments, centroids and Rand indices comparing pairs of partitions.

Usage

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

Arguments

x, k, ...	Passed to ockc
nboot	Number of bootstrap pairs (maintaining order).
order	Order restriction of x. If NULL an initial run of ockc with order=NULL is run to calculate an order with seriate from package seriation
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	Use parallelization, if available. For examples and additional documentation see bootFlexclust.
verbose	Logical, show progress information during computations. Ignored if multicore=TRUE.

Value

Returns an object of class "bootFlexclust".

Author(s)

Sebastian Krey

See Also

ockc, bootFlexclust, stepFlexclust

Examples

x <- rbind(cbind(rnorm(10, mean=0), rnorm(10, mean=0,), rnorm(10, mean=0)),
           cbind(rnorm(10, mean=10), rnorm(10, mean=10), rnorm(10, mean=0)),
           cbind(rnorm(10, mean=10), rnorm(10, mean=0), rnorm(10, mean=10)),
           cbind(rnorm(10, mean=10), rnorm(10, mean=10), rnorm(10, mean=10))
           )

bockc <- bootockc(x, 2:4, nboot=4, order=c(1:10, 21:40, 11:20),
                  multicore=FALSE, verbose=FALSE)
bockc

ockc documentation built on Dec. 28, 2022, 2:18 a.m.