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.
Package details |
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| Author | Bradley Buchsbaum [aut, cre, cph] |
| Maintainer | Bradley Buchsbaum <brad.buchsbaum@gmail.com> |
| License | MIT + file LICENSE |
| Version | 1.0.2 |
| URL | https://bbuchsbaum.github.io/eigencore/ https://github.com/bbuchsbaum/eigencore |
| Package repository | View on CRAN |
| Installation |
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