Solvers for Large-Scale Eigenvalue and SVD Problems R package RSpectra version 0.16-2 CRAN Task View: NumericalMathematics (https://CRAN.R-project.org/view=NumericalMathematics) 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. Software 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 Yixuan Qiu <yixuan.qiu@cos.name> Comprehensive R Archive Network (CRAN) 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) MPL (>= 2) 2024-07-18 application/tgz https://CRAN.R-project.org/package=RSpectra doi:10.32614/CRAN.package.RSpectra