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.
- Version1.0.1
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- tensr citation info
- Last release08/15/2018
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David Gerard
Peter Hoff
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