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eigencore

Certified Partial Eigenvalue and Singular Value Computation

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.

Versions across snapshots

VersionRepositoryFileSize
1.0.0 rolling linux/jammy R-4.5 eigencore_1.0.0.tar.gz 3.0 MiB
1.0.0 rolling linux/noble R-4.5 eigencore_1.0.0.tar.gz 3.0 MiB
1.0.0 rolling source/ R- eigencore_1.0.0.tar.gz 3.1 MiB
1.0.0 latest linux/jammy R-4.5 eigencore_1.0.0.tar.gz 3.0 MiB
1.0.0 latest linux/noble R-4.5 eigencore_1.0.0.tar.gz 3.0 MiB
1.0.0 latest source/ R- eigencore_1.0.0.tar.gz 3.1 MiB
1.0.0 2026-04-23 source/ R- eigencore_1.0.0.tar.gz 0 B

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