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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) <doi:10.48550/arXiv.1806.10093>.

Version: 0.1.1
Imports: Matrix, stats, Rdpack, BBmisc, dplyr, tibble, magrittr, rlang
Suggests: knitr
Published: 2019-04-13
DOI: 10.32614/CRAN.package.BlockCov
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

Documentation:

Reference manual: BlockCov.pdf
Vignettes: BlockCov package

Downloads:

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
macOS binaries: r-release (arm64): BlockCov_0.1.1.tgz, r-oldrel (arm64): BlockCov_0.1.1.tgz, r-release (x86_64): BlockCov_0.1.1.tgz, r-oldrel (x86_64): BlockCov_0.1.1.tgz
Old sources: BlockCov archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=BlockCov to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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