Package: eigencore
Title: Certified Partial Eigenvalue and Singular Value Computation
Version: 1.0.2
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: 2026-07-25 12:00:52 UTC; bbuchsbaum
Repository: CRAN
Date/Publication: 2026-07-25 22:00:03 UTC
Built: R 4.5.3; x86_64-w64-mingw32; 2026-08-03 21:28:23 UTC; windows
Archs: x64
