tensr

tensr-package

<img src="figures/logo.png?package=tensr&version=1.0.2" style="float: right" alt="logo" width="120">
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) tools:::Rd_expr_doi("10.1016/j.jmva.2015.01.020") and Gerard and Hoff (2016) tools:::Rd_expr_doi("10.1016/j.laa.2016.04.033").

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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>.

David Gerard

Covariance Inference and Decompositions for Tensor Datasets

Peter Hoff

tensr-package function

Maintainer: David Gerard <a href="/link/gerard.1787%40gmail.com?package=tensr&version=1.0.2" data-mini-rdoc="tensr::gerard.1787@gmail.com">gerard.1787@gmail.com</a> (<a href="https://orcid.org/0000-0001-9450-5023">ORCID</a>)
Authors:<ul>
<li>Peter Hoff <a href="/link/peter.hoff%40duke.edu?package=tensr&version=1.0.2" data-mini-rdoc="tensr::peter.hoff@duke.edu">peter.hoff@duke.edu</a></li>
</ul>

Author

<img src='figures/logo.png' style='float: right' alt='logo' width='120' />
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) tools:::Rd_expr_doi("10.1016/j.jmva.2015.01.020") and Gerard and Hoff (2016) tools:::Rd_expr_doi("10.1016/j.laa.2016.04.033").

tensr: Covariance Inference and Decompositions for Tensor Datasets — tensr-package

Maintainer: David Gerard <a href='mailto:gerard.1787@gmail.com'>gerard.1787@gmail.com</a> (<a href='https://orcid.org/0000-0001-9450-5023'>ORCID</a>)
Authors:<ul>
<li>Peter Hoff <a href='mailto:peter.hoff@duke.edu'>peter.hoff@duke.edu</a></li>
</ul>

tensr-package: tensr: Covariance Inference and Decompositions for Tensor Datasets

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