BlockCov: Estimation of Large Block Covariance Matrices

Computation of large covariance matrices having a block structure up to a permutation of their columns and rows from a small number of samples with respect to the dimension of the matrix. The method is described in the paper Perrot-Dockès et al. (2019) <arXiv:1806.10093>.

Version: 0.1.1
Imports: Matrix, stats, Rdpack, BBmisc, dplyr, tibble, magrittr, rlang
Suggests: knitr
Published: 2019-04-13
Author: M. Perrot-Dock\`es, C. Lévy-Leduc
Maintainer: Marie Perrot-Dockès <marie.perrocks at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: BlockCov results

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Reference manual: BlockCov.pdf
Vignettes: BlockCov package
Package source: BlockCov_0.1.1.tar.gz
Windows binaries: r-devel: BlockCov_0.1.1.zip, r-release: BlockCov_0.1.1.zip, r-oldrel: BlockCov_0.1.1.zip
OS X binaries: r-release: BlockCov_0.1.1.tgz, r-oldrel: BlockCov_0.1.0.tgz
Old sources: BlockCov archive

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