Package: matsketch
Title: Randomized Matrix Computations from Few Entries and Products
Version: 0.1.0
Authors@R: 
    person("Muhammad", "Farooqi", email = "mqfarooqi@gmail.com",
           role = c("aut", "cre"),
           comment = c(ORCID = "0000-0003-4918-9791"))
Description: Implements recent randomized algorithms that answer questions
    about a large positive-semidefinite matrix while touching only a small
    part of it. Randomly pivoted Cholesky builds a low-rank approximation
    from a few rows of a kernel matrix (Chen, Epperly, Tropp and Webber
    (2025) <doi:10.1002/cpa.22234>), with an accelerated variant based on
    rejection sampling (Epperly, Tropp and Webber (2025)
    <doi:10.1137/24m1699048>). The XTrace, XNysTrace and XDiag estimators
    recover the trace and diagonal of a matrix that is available only
    through matrix-vector products (Epperly, Tropp and Webber (2024)
    <doi:10.1137/23m1548323>), alongside the Hutch++ estimator of Meyer,
    Musco, Musco and Woodruff (2021) <doi:10.1137/1.9781611976496.16>.
    Randomized Nystrom preconditioning speeds up the conjugate gradient
    method for regularized linear systems (Frangella, Tropp and Udell (2023)
    <doi:10.1137/21m1466244>). These pieces are combined to fit restricted
    maximum likelihood variance-component models on genomic relationship
    matrices without forming or factorizing the covariance matrix.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: graphics, grDevices, stats
Suggests: knitr, Matrix, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
URL: https://github.com/mqfarooqi1/matsketch,
        https://mqfarooqi1.github.io/matsketch/
BugReports: https://github.com/mqfarooqi1/matsketch/issues
Config/roxygen2/version: 8.1.0
NeedsCompilation: no
Packaged: 2026-09-11 01:03:34 UTC; faroo
Author: Muhammad Farooqi [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-4918-9791>)
Maintainer: Muhammad Farooqi <mqfarooqi@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-21 17:20:02 UTC
