Package: tensorEVD 0.1.4

Marco Lopez-Cruz

tensorEVD: A Fast Algorithm to Factorize High-Dimensional Tensor Product Matrices

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>.

Authors:Marco Lopez-Cruz [aut, cre], Gustavo de los Campos [aut], Paulino Perez-Rodriguez [aut]

tensorEVD_0.1.4.tar.gz
tensorEVD_0.1.4.zip(r-4.5)tensorEVD_0.1.4.zip(r-4.4)tensorEVD_0.1.4.zip(r-4.3)
tensorEVD_0.1.4.tgz(r-4.4-x86_64)tensorEVD_0.1.4.tgz(r-4.4-arm64)tensorEVD_0.1.4.tgz(r-4.3-x86_64)tensorEVD_0.1.4.tgz(r-4.3-arm64)
tensorEVD_0.1.4.tar.gz(r-4.5-noble)tensorEVD_0.1.4.tar.gz(r-4.4-noble)
tensorEVD_0.1.4.tgz(r-4.4-emscripten)tensorEVD_0.1.4.tgz(r-4.3-emscripten)
tensorEVD.pdf |tensorEVD.html
tensorEVD/json (API)
NEWS

# Install 'tensorEVD' in R:
install.packages('tensorEVD', repos = c('https://marcoolopez.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/marcoolopez/tensorevd/issues

On CRAN:

6 exports 2 stars 1.57 score 0 dependencies 1 dependents 9 scripts 843 downloads

Last updated 15 days agofrom:45a8ae5d5b. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 03 2024
R-4.5-win-x86_64OKSep 03 2024
R-4.5-linux-x86_64OKSep 03 2024
R-4.4-win-x86_64OKSep 03 2024
R-4.4-mac-x86_64OKSep 03 2024
R-4.4-mac-aarch64OKSep 03 2024
R-4.3-win-x86_64OKSep 03 2024
R-4.3-mac-x86_64OKSep 03 2024
R-4.3-mac-aarch64OKSep 03 2024

Exports:HadamardHadamard_covKroneckerKronecker_covSumtensorEVD

Dependencies:

Documentation: A fast algorithm to factorize high-dimensional Tensor Product matrices used in Genetic Models

Rendered fromtensorEVD-documentation.Rmdusingknitr::rmarkdownon Sep 03 2024.

Last update: 2024-09-03
Started: 2023-11-13