Certified Partial Eigenvalue and Singular Value Computation R package eigencore version 1.0.3 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. Software Depends: R (>= 4.1) Imports: Matrix, methods Suggests: bench, knitr, rmarkdown, RSpectra, irlba, rsvd, testthat (>= 3.0.0) Bradley Buchsbaum <brad.buchsbaum@gmail.com> Comprehensive R Archive Network (CRAN) Bradley Buchsbaum [aut, cre, cph] MIT + file LICENSE (https://CRAN.R-project.org/package=eigencore/LICENSE) 2026-08-26 application/tgz https://CRAN.R-project.org/package=eigencore doi:10.32614/CRAN.package.eigencore