eigencore
1.0.2Certified Partial Eigenvalue and Singular Value Computation
Overview
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.
Install
Health
- ERROR r-release-linux-x86_64
- ERROR2026-07-245 OK · 0 NOTE · 0 WARNING · 2 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
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- Return-value docs
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- References docs
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Checks run against github.com/bbuchsbaum/eigencore on 2026-07-30.
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Code & Tests
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3 releases. Pick two to compare their code metrics. R releases are shown for context.
- 1.0.2Latest
- 1.0.12026-07-25 · diff ↗
- 1.0.02026-07-23
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-07-23
- Total releases
- 3 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 4.1
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet