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 |
| Reference manual: | BlockCov.html ,BlockCov.pdf |
| Vignettes: | BlockCov package (source,R code) |
| 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 |
Please use the canonical formhttps://CRAN.R-project.org/package=BlockCovto link to this page.