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.
| Version: | 0.16-1 |
| Depends: | R (≥ 3.0.2) |
| Imports: | Matrix (≥ 1.1-0), Rcpp (≥ 0.11.5) |
| LinkingTo: | Rcpp, RcppEigen (≥ 0.3.3.3.0) |
| Suggests: | knitr, rmarkdown, prettydoc |
| Published: | 2022-04-24 |
| 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 at cos.name> |
| BugReports: | https://github.com/yixuan/RSpectra/issues |
| License: | MPL (≥ 2) |
| URL: | https://github.com/yixuan/RSpectra |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| In views: | NumericalMathematics |
| CRAN checks: | RSpectra results |
| Reference manual: | RSpectra.pdf |
| Vignettes: |
Large-Scale Eigenvalue Decomposition and SVD with RSpectra |
| Package source: | RSpectra_0.16-1.tar.gz |
| Windows binaries: | r-devel: RSpectra_0.16-1.zip, r-release: RSpectra_0.16-1.zip, r-oldrel: RSpectra_0.16-1.zip |
| macOS binaries: | r-release (arm64): RSpectra_0.16-1.tgz, r-oldrel (arm64): RSpectra_0.16-1.tgz, r-release (x86_64): RSpectra_0.16-1.tgz, r-oldrel (x86_64): RSpectra_0.16-1.tgz |
| Old sources: | RSpectra archive |
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