The 'tensorEVD' R-package offers tools for calculation and factorization of high-dimensional tensor products (Hadamard and Kronecker) that are formed by smaller matrices.
Funding: NSF PGRP-Tech Grant 2035472.
Last update: May 22, 2024
Installation of 'tensorEVD' package requires an R-version ≥ 3.6.0.
From CRAN (stable version)
install.packages('tensorEVD', repos='https://cran.r-project.org/')
library(tensorEVD)
From GitHub (developing version)
if(!'remotes' %in% rownames(installed.packages())){
install.packages('remotes', repos='https://cran.r-project.org/')
}
remotes::install_github('MarcooLopez/tensorEVD')
library(tensorEVD)
Description of the package's main functions.
help(package='tensorEVD', help_type='html')
Here we present examples on the use of the functions included in the package.
We provide benchmarks and an application in Genomic Prediction of the tensorEVD() function using data from the Genomes-to-Field (G2F) Initiative
- Lopez-Cruz et al., 2024. G3:Genes|Genomes|Genetics [Manuscript] [Documentation]
Lopez-Cruz M, Pérez-Rodríguez Paulino, and de los Campos G. 2024. A fast algorithm to factorize high-dimensional Tensor Product matrices used in Genetic Models. G3 Genes|Genomes|Genetics 14(3): 1-8. doi: 10.1093/g3journal/jkae001