tensr: Covariance Inference and Decompositions for Tensor Datasets

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>.

Package details

AuthorDavid Gerard [aut, cre] (<https://orcid.org/0000-0001-9450-5023>), Peter Hoff [aut]
MaintainerDavid Gerard <[email protected]>
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the tensr package in your browser

Any scripts or data that you put into this service are public.

tensr documentation built on Aug. 16, 2018, 1:04 a.m.