Solvers for Large-Scale Eigenvalue and SVD Problems

R interface to the 'Spectra' library <> 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.

Tests Vignettes

Available Snapshots

This version of RSpectra can be found in the following snapshots:


Imports/Depends/LinkingTo/Enhances (4)
  • R
  • Rcpp >= 0.11.5
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  • RcppEigen >=
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