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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.2 |
rolling linux/jammy R-4.5 | tensr_1.0.2.tar.gz |
516.8 KiB |
1.0.2 |
rolling linux/noble R-4.5 | tensr_1.0.2.tar.gz |
516.9 KiB |
1.0.2 |
rolling source/ R- | tensr_1.0.2.tar.gz |
378.4 KiB |
1.0.2 |
latest linux/jammy R-4.5 | tensr_1.0.2.tar.gz |
516.8 KiB |
1.0.2 |
latest linux/noble R-4.5 | tensr_1.0.2.tar.gz |
516.9 KiB |
1.0.2 |
latest source/ R- | tensr_1.0.2.tar.gz |
378.4 KiB |
1.0.2 |
2026-04-26 source/ R- | tensr_1.0.2.tar.gz |
378.4 KiB |
1.0.2 |
2026-04-23 source/ R- | tensr_1.0.2.tar.gz |
378.4 KiB |
1.0.2 |
2026-04-09 windows/windows R-4.5 | tensr_1.0.2.zip |
523.8 KiB |
1.0.1 |
2025-04-20 source/ R- | tensr_1.0.1.tar.gz |
113.4 KiB |