Package: eigencore
Title: Certified Partial Eigenvalue and Singular Value Computation
Version: 1.0.0
Authors@R: c(
    person("Bradley", "Buchsbaum", role = c("aut", "cre", "cph"), email = "brad.buchsbaum@gmail.com")
  )
Author: Bradley Buchsbaum [aut, cre, cph]
Maintainer: Bradley Buchsbaum <brad.buchsbaum@gmail.com>
Description: Computes the top-k singular triplets or eigenpairs of
        large sparse and structured matrices: the computation behind
        principal component analysis on big sparse data, spectral
        embeddings, and low-rank approximation. Every result carries a
        numerical certificate with residuals, a backward-error bound,
        orthogonality loss, and a pass/fail flag, and bounds that can
        only be estimated are reported as such rather than passed.
        Centered, scaled, and composed operators are solved through
        native 'C++' kernels without forming dense matrices. Drop-in
        replacements for the 'RSpectra' interface are included.
URL: https://bbuchsbaum.github.io/eigencore/,
        https://github.com/bbuchsbaum/eigencore
BugReports: https://github.com/bbuchsbaum/eigencore/issues
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Depends: R (>= 4.1)
Imports: Matrix, methods
Suggests: bench, knitr, rmarkdown, RSpectra, irlba, rsvd, testthat (>=
        3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
SystemRequirements: C++17
Config/Needs/website: albersdown
NeedsCompilation: yes
Packaged: 2026-07-23 17:12:34 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2026-07-23 14:10:02 UTC
RemoteUrl: https://github.com/cran/eigencore
RemoteRef: HEAD
RemoteSha: 9cc2662e60e5599cdaf218efbf3fe62da79998a2