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.
- Version0.16-2
- R version≥ 3.0.2
- LicenseMPL (≥ 2)
- Needs compilation?Yes
- Last release07/18/2024
Documentation
Team
Yixuan Qiu
Gael Guennebaud
Show author detailsRolesContributorJitse Niesen
Show author detailsRolesContributorJiali Mei
Show author detailsRolesAuthor
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