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) ), with an accelerated variant based on rejection sampling (Epperly, Tropp and Webber (2025) ). 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) ), alongside the Hutch++ estimator of Meyer, Musco, Musco and Woodruff (2021) . Randomized Nystrom preconditioning speeds up the conjugate gradient method for regularized linear systems (Frangella, Tropp and Udell (2023) ). 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: 2026-09-21 21:19:33 UTC; root Author: Muhammad Farooqi [aut, cre] (ORCID: ) Maintainer: Muhammad Farooqi Repository: https://cran.r-universe.dev Date/Publication: 2026-09-21 19:36:04 UTC RemoteUrl: https://github.com/cran/matsketch RemoteRef: HEAD RemoteSha: 330ad41b699ee992570a88531e4ad45a5e0fa84b