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tensr

Covariance Inference and Decompositions for Tensor Datasets

v1.0.2 · Jul 24, 2025 · GPL-3

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>.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Reverse Dependencies (4)

Dependency Network

Dependencies Reverse dependencies assertthat TULIP TensorClustering catch hwep tensr

Version History

new 1.0.2 Mar 9, 2026