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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.
Getting started
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Package details |
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| Author | Yixuan Qiu [aut, cre], Jiali Mei [aut] (Function interface of matrix operation), Gael Guennebaud [ctb] (Eigenvalue solvers from the 'Eigen' library), Jitse Niesen [ctb] (Eigenvalue solvers from the 'Eigen' library) |
| Maintainer | Yixuan Qiu <yixuan.qiu@cos.name> |
| License | MPL (>= 2) |
| Version | 0.16-1 |
| URL | https://github.com/yixuan/RSpectra |
| Package repository | View on CRAN |
| Installation |
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