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tensorEVD  

A Fast Algorithm to Factorize High-Dimensional Tensor Product Matrices
View on CRAN: Click here


Download and install tensorEVD package within the R console
Install from CRAN:
install.packages("tensorEVD")

Install from Github:
library("remotes")
install_github("cran/tensorEVD")

Install by package version:
library("remotes")
install_version("tensorEVD", "0.1.4")



Attach the package and use:
library("tensorEVD")
Maintained by
Marco Lopez-Cruz
[Scholar Profile | Author Map]
First Published: 2023-11-14
Latest Update: 2024-02-08
Description:
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>.
How to cite:
Marco Lopez-Cruz (2023). tensorEVD: A Fast Algorithm to Factorize High-Dimensional Tensor Product Matrices. R package version 0.1.4, https://cran.r-project.org/web/packages/tensorEVD. Accessed 06 Apr. 2025.
Previous versions and publish date:
0.1.0 (2023-11-14 18:20), 0.1.1 (2024-02-08 23:10), 0.1.2 (2024-05-22 23:10), 0.1.3 (2024-05-30 09:10)
Other packages that cited tensorEVD R package
View tensorEVD citation profile
Other R packages that tensorEVD depends, imports, suggests or enhances
Complete documentation for tensorEVD
Functions, R codes and Examples using the tensorEVD R package
Some associated functions: hadamard . kronecker . kronecker_covariance . tensorEVD . 
Some associated R codes: Hadamard.R . Kronecker.R . Kronecker_cov.R . rrr_functions.R . tensorEVD.R .  Full tensorEVD package functions and examples
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