iTensor: ICA-Based Matrix/Tensor Decomposition

Some functions for performing ICA, MICA, Group ICA, and Multilinear ICA are implemented. ICA, MICA/Group ICA, and Multilinear ICA extract statistically independent components from single matrix, multiple matrices, and single tensor, respectively. For the details of these methods, see the reference section of GitHub README.md <https://github.com/rikenbit/iTensor>.

Version:	1.0.2
Depends:	R (≥ 4.1.0)
Imports:	MASS, methods, graphics, utils, stats, rTensor, jointDiag, mgcv, einsum, geigen, mixOmics, groupICA
Suggests:	nnTensor, knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2023-04-28
DOI:	10.32614/CRAN.package.iTensor
Author:	Koki Tsuyuzaki [aut, cre]
Maintainer:	Koki Tsuyuzaki <k.t.the-answer at hotmail.co.jp>
License:	MIT + file LICENSE
URL:	https://github.com/rikenbit/iTensor
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	iTensor results

Documentation:

Reference manual:	iTensor.html , iTensor.pdf
Vignettes:	1. Independent Component Analysis (ICA) (source, R code) 2. Multimodal Independent Component Analysis (MICA) and Group Independent Component Analysis (GroupICA) (source, R code) 3. Multilinear Independent Component Analysis (MultilinearICA) (source, R code)

Downloads:

Package source:	iTensor_1.0.2.tar.gz
Windows binaries:	r-devel: iTensor_1.0.2.zip, r-release: iTensor_1.0.2.zip, r-oldrel: iTensor_1.0.2.zip
macOS binaries:	r-release (arm64): iTensor_1.0.2.tgz, r-oldrel (arm64): iTensor_1.0.2.tgz, r-release (x86_64): iTensor_1.0.2.tgz, r-oldrel (x86_64): iTensor_1.0.2.tgz
Old sources:	iTensor archive

Reverse dependencies:

Reverse imports:

mwTensor

Linking:

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