Package: RSpectra 0.16-2

RSpectra: Solvers for Large-Scale Eigenvalue and SVD Problems

R interface to the 'Spectra' library <https://spectralib.org/> for large-scale eigenvalue and SVD problems. It is typically used to compute a few eigenvalues/vectors of an n by n matrix, e.g., the k largest eigenvalues, which is usually more efficient than eigen() if k << n. This package provides the 'eigs()' function that does the similar job as in 'Matlab', 'Octave', 'Python SciPy' and 'Julia'. It also provides the 'svds()' function to calculate the largest k singular values and corresponding singular vectors of a real matrix. The matrix to be computed on can be dense, sparse, or in the form of an operator defined by the user.

Authors:Yixuan Qiu [aut, cre], Jiali Mei [aut], Gael Guennebaud [ctb], Jitse Niesen [ctb]

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NEWS

Peer review:

Bug tracker:https://github.com/yixuan/rspectra/issues

On CRAN:

eigenvaluesspectrasvd

3 exports 80 stars 9.79 score 4 dependencies 397 dependents 1 mentions 332 scripts 62.4k downloads

Last updated 2 months agofrom:8bdd2e9104. Checks:OK: 9. Indexed: yes.

Exports:eigseigs_symsvds

Dependencies:latticeMatrixRcppRcppEigen