RSpectra: Solvers for Large-Scale Eigenvalue and SVD Problems

R interface to the 'Spectra' library &lt;<a href="https://spectralib.org/" target="_top">https://spectralib.org/</a>&gt; 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 &lt;&lt; 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.