CICA: CICA: Clusterwise Independent Component Analysis

In CICA: Clusterwise Independent Component Analysis

Description

Main function to perform Clusterwise Independent Component Analysis

Usage

CICA(
  DataList,
  nStarts,
  nComp,
  nClus,
  scale = TRUE,
  center = TRUE,
  rational = NULL,
  maxiter = 100,
  verbose = TRUE
)

Arguments

DataList	a list of matrices
nStarts	number of multiple starts
nComp	number of ICA components per cluster
nClus	number of clusters
scale	scale each matrix to have an equal sum of squares
center	mean center matrices
rational	a rational starting seed, if NULL no rational starting seed is used
maxiter	maximum number of iterations for each start
verbose	print loss information to console

Value

CICA returns an object of class "CICA". It contains the estimated clustering, cluster specific component matrices and subject specific time course matrices

P	partitioning vector of size length(DataList)
Sr	list of size nClus, containing cluster specific independent components
Ais	list of size length(DataList), containing subject specific time courses
Loss	loss function value of the best start
LossStarts	loss function values of all starts

Author(s)

Jeffrey Durieux

Examples

data('ExampleData', package = 'CICA')
output <- CICA(DataList = ExampleData, nStarts = 3, nComp = 5, nClus = 3, verbose = FALSE)
summary(output)

CICA documentation built on July 1, 2021, 9:07 a.m.