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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 |
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 imports: | mwTensor |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.