microSTASIS (version 0.1.0)

iterative_clustering: Iterative Hartigan-Wong k-means clustering.

Description

Perform Hartigan-Wong stats::kmeans() algorithm as many times as possible. The values of k are from 2 to the number of rows minus 1.

Usage

iterative_clustering(data, parallel = TRUE)

Arguments

data

input matrix with paired times, i.e. samples to be stressed to multiple iterations.

parallel

logical; FALSE to sequentially run the internal loop or TRUE to do it by parallel computing (number of cores = 4).

Value

A list with multiple objects of class "kmeans".

Examples

# NOT RUN {
t1_t2 <- paired_times(data = clr[,1:50], first = "_1",
                      second = "_25", common = "_0_")
klist_t1_t2 <- iterative_clustering(data = t1_t2, parallel = FALSE)
# }