cvCovEst: Cross-Validated Covariance Matrix Estimation

An efficient cross-validated approach for covariance matrix estimation, particularly useful in high-dimensional settings. This method relies upon the theory of high-dimensional loss-based covariance matrix estimator selection developed by Boileau et al. (2022) <doi:10.1080/10618600.2022.2110883> to identify the optimal estimator from among a prespecified set of candidates.

Version: 1.2.2
Depends: R (≥ 4.0.0)
Imports: matrixStats, Matrix, stats, methods, origami, coop, Rdpack, rlang, dplyr, stringr, purrr, tibble, assertthat, RSpectra, ggplot2, ggpubr, RColorBrewer, RMTstat
Suggests: future, future.apply, MASS, testthat, knitr, rmarkdown, covr, spelling
Published: 2024-02-17
DOI: 10.32614/CRAN.package.cvCovEst
Author: Philippe Boileau ORCID iD [aut, cre, cph], Nima Hejazi ORCID iD [aut], Brian Collica ORCID iD [aut], Jamarcus Liu [ctb], Mark van der Laan ORCID iD [ctb, ths], Sandrine Dudoit ORCID iD [ctb, ths]
Maintainer: Philippe Boileau <philippe_boileau at>
License: MIT + file LICENSE
NeedsCompilation: no
Language: en-US
Citation: cvCovEst citation info
Materials: README NEWS
CRAN checks: cvCovEst results


Reference manual: cvCovEst.pdf
Vignettes: cvCovEst: Cross-Validated Covariance Matrix Estimation


Package source: cvCovEst_1.2.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): cvCovEst_1.2.2.tgz, r-oldrel (arm64): cvCovEst_1.2.2.tgz, r-release (x86_64): cvCovEst_1.2.2.tgz, r-oldrel (x86_64): cvCovEst_1.2.2.tgz
Old sources: cvCovEst archive

Reverse dependencies:

Reverse imports: PPLasso, WLogit
Reverse suggests: bdsvd


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