Here we provide tools for the computation and factorization of high-dimensional tensor products that are formed by smaller matrices. The methods are based on properties of Kronecker products (Searle 1982, p. 265, ISBN-10: 0470009616). We evaluated this methodology by benchmark testing and illustrated its use in Gaussian Linear Models ('Lopez-Cruz et al., 2024') <doi:10.1093/g3journal/jkae001>.
Version: | 0.1.4 |
Depends: | R (≥ 3.6.0) |
Suggests: | knitr, rmarkdown, ggplot2, ggnewscale, reshape2, RColorBrewer, pryr |
Published: | 2024-09-03 |
DOI: | 10.32614/CRAN.package.tensorEVD |
Author: | Marco Lopez-Cruz [aut, cre], Gustavo de los Campos [aut], Paulino Perez-Rodriguez [aut] |
Maintainer: | Marco Lopez-Cruz <maraloc at gmail.com> |
License: | GPL-3 |
URL: | https://github.com/MarcooLopez/tensorEVD |
NeedsCompilation: | yes |
Citation: | tensorEVD citation info |
Materials: | NEWS |
CRAN checks: | tensorEVD results |
Reference manual: | tensorEVD.pdf |
Vignettes: |
Documentation: A fast algorithm to factorize high-dimensional tensor product matrices (source, R code) |
Package source: | tensorEVD_0.1.4.tar.gz |
Windows binaries: | r-devel: tensorEVD_0.1.4.zip, r-release: tensorEVD_0.1.4.zip, r-oldrel: tensorEVD_0.1.4.zip |
macOS binaries: | r-release (arm64): tensorEVD_0.1.4.tgz, r-oldrel (arm64): tensorEVD_0.1.4.tgz, r-release (x86_64): tensorEVD_0.1.4.tgz, r-oldrel (x86_64): tensorEVD_0.1.4.tgz |
Old sources: | tensorEVD archive |
Reverse imports: | SFSI |
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