DESCRIPTION

Package: cvCovEst
Title: Cross-Validated Covariance Matrix Estimation
Version: 1.2.2
Authors@R: c(
    person("Philippe", "Boileau", email = "philippe_boileau@berkeley.edu",
           role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0002-4850-2507")),
    person("Nima", "Hejazi", email = "nh@nimahejazi.org",
           role = "aut",
           comment = c(ORCID = "0000-0002-7127-2789")),
    person("Brian", "Collica", email = "bcollica@berkeley.edu ",
           role = "aut",
           comment = c(ORCID = "0000-0003-1127-2557")),
    person("Jamarcus", "Liu", email = "yanwei.liu@berkeley.edu ",
           role = "ctb"),
    person("Mark", "van der Laan", email = "laan@berkeley.edu",
           role = c("ctb", "ths"),
           comment = c(ORCID = "0000-0003-1432-5511")),
    person("Sandrine", "Dudoit", email = "sandrine@stat.berkeley.edu",
           role = c("ctb", "ths"),
           comment = c(ORCID = "0000-0002-6069-8629"))
  )
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.
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
License: MIT + file LICENSE
URL: https://github.com/PhilBoileau/cvCovEst
BugReports: https://github.com/PhilBoileau/cvCovEst/issues
Encoding: UTF-8
LazyData: false
VignetteBuilder: knitr
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1
RdMacros: Rdpack
Language: en-US