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>.
Last updated 2 years ago
6.48 score 5 stars 4 packages 50 scripts 202 downloadssegtest - Tests for Segregation Distortion in Polyploids
Provides a suite of tests for segregation distortion in F1 polyploid populations (for now, just tetraploids). This is under different assumptions of meiosis. Details of these methods are described in Gerard et al. (2024) <doi:10.1101/2024.02.07.579361>. This material is based upon work supported by the National Science Foundation under Grant No. 2132247. The opinions, findings, and conclusions or recommendations expressed are those of the author and do not necessarily reflect the views of the National Science Foundation.
Last updated 1 months ago
4.78 score 1 stars 3 scripts 211 downloads