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>.
| Version: | 1.0.1 |
| Imports: | assertthat |
| Suggests: | knitr, rmarkdown, covr, testthat |
| Published: | 2018-08-15 |
| DOI: | 10.32614/CRAN.package.tensr |
| Author: | David Gerard |
| Maintainer: | David Gerard <gerard.1787 at gmail.com> |
| BugReports: | http://github.com/dcgerard/tensr/issues |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Citation: | tensr citation info |
| Materials: | README |
| CRAN checks: | tensr results |
Documentation:
| Reference manual: | tensr.pdf |
| Vignettes: |
Equivariant Estimation Likelihood Inference |
Downloads:
| Package source: | tensr_1.0.1.tar.gz |
| Windows binaries: | r-devel: tensr_1.0.1.zip, r-release: tensr_1.0.1.zip, r-oldrel: tensr_1.0.1.zip |
| macOS binaries: | r-release (arm64): tensr_1.0.1.tgz, r-oldrel (arm64): tensr_1.0.1.tgz, r-release (x86_64): tensr_1.0.1.tgz, r-oldrel (x86_64): tensr_1.0.1.tgz |
| Old sources: | tensr archive |
Reverse dependencies:
| Reverse imports: | catch, hwep, TensorClustering, TULIP |
Linking:
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