_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-cvcovest 1.2.2
Propagated dependencies: r-tibble@3.2.1 r-stringr@1.5.1 r-rspectra@0.16-2 r-rmtstat@0.3.1 r-rlang@1.1.4 r-rdpack@2.6.1 r-rcolorbrewer@1.1-3 r-purrr@1.0.2 r-origami@1.0.7 r-matrixstats@1.4.1 r-matrix@1.7-1 r-ggpubr@0.6.0 r-ggplot2@3.5.1 r-dplyr@1.1.4 r-coop@0.6-3 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/PhilBoileau/cvCovEst
Licenses: Expat
Synopsis: Cross-Validated Covariance Matrix Estimation
Description:

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.

Total results: 1