orc.lsbclust {lsbclust}

K-means on the Overall Mean, Row Margins or Column Margins

Description

This function conducts k-means on the overall mean, the row margins or column margins of a set of N matrices. These matrices are two-way slices of a three-dimensional array.

Usage

orc.lsbclust(data, margin = 3L, delta, nclust, sep.nclust = TRUE,
  type = NULL, verbose = 1, ...)

Arguments

data

A three-way array representing the data.

margin

An integer giving the single subscript of data over which the clustering will be applied.

delta

A four-element binary vector (logical or numeric) indicating which sum-to-zero constraints must be enforced.

nclust

An integer giving the desired number of clusters. In case type specifies more than one method, nclust can be a vector containing the number of clusters to be determined for each type of cluster, and in the correct order as determined by type (after matching the arguments). If type is of length greater than one and nclust is of length one, the behaviour is governed by sep.nclust.

sep.nclust

Logical indicating how nclust should be used across different type's. If sep.nclust is TRUE, nclust is recycled so that each type can have a different number of clusters. If sep.nclust is FALSE, the same vector nclust is used for all type's.

type

One of "overall", "rows" or "columns" (or a unique abbreviation of one of these) indicating whether clustering should be done on row margins, column margins or the overall means of the two-way slices respectively. If more than one opion are supplied, the algorithm is run for all (unique) options supplied.

verbose

Integer controlling the amount of information printed: 0 = no information, 1 = Information on random starts and progress, and 2 = information is printed after each iteration for the interaction clustering.

...

Additional arguments passed to kmeans.

Value

A list containing a subset of the classes row.kmeans, col.kmeans and ovl.kmeans which are specific versions of class kmeans. In case type is a vector, a list is returned containing the results for each of the (unique) elements of type, with the same classes as before. See kmeans for an overview of the structure of these objects.

See Also

kmeans