rARPACK (0.9-0)

Solvers for Large Scale Eigenvalue and SVD Problems.


An R wrapper of the 'ARPACK' library to solve large scale eigenvalue/vector 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 which 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. Matrices can be given in either dense or sparse form.

Maintainer: Yixuan Qiu
Author(s): Yixuan Qiu, Jiali Mei and authors of the ARPACK library. See file AUTHORS for details.

License: BSD_3_clause + file LICENSE

Uses: Matrix, Rcpp
Reverse depends: FastKM, Gmedian, lori, onlinePCA, POINT, PPCI
Reverse suggests: logisticPCA, MFKnockoffs

Released almost 4 years ago.