tensorEVD: A Fast Algorithm to Factorize High-Dimensional Tensor Product Matrices (original) (raw)
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 |
| License: | GPL-3 |
| URL: | https://github.com/MarcooLopez/tensorEVD |
| NeedsCompilation: | yes |
| Citation: | tensorEVD citation info |
| Materials: | NEWS |
| CRAN checks: | tensorEVD results |
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