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tensr  

Covariance Inference and Decompositions for Tensor Datasets
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("tensr", "1.0.1")



Attach the package and use:
library("tensr")
Maintained by
David Gerard
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-02-03
Latest Update: 2018-08-15
Description:
A collection of functions for Kronecker structured covariance estimation and testing under the array normal model. For estimation, maximum likelihood and Bayesian equivariant estimation procedures are implemented. For testing, a likelihood ratio testing procedure is available. This package also contains additional functions for manipulating and decomposing tensor data sets. This work was partially supported by NSF grant DMS-1505136. Details of the methods are described in Gerard and Hoff (2015) <doi:10.1016/j.jmva.2015.01.020> and Gerard and Hoff (2016) <doi:10.1016/j.laa.2016.04.033>.
How to cite:
David Gerard (2016). tensr: Covariance Inference and Decompositions for Tensor Datasets. R package version 1.0.1, https://cran.r-project.org/web/packages/tensr
Previous versions and publish date:
1.0.0 (2016-02-03 22:04)
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