RSpectra

Solvers for Large-Scale Eigenvalue and SVD Problems

CRAN Package

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.

  • Version0.16-2
  • R version≥ 3.0.2
  • LicenseMPL (≥ 2)
  • Needs compilation?Yes
  • Last release07/18/2024

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