## RSpectra: Solvers for Large-Scale Eigenvalue and SVD Problems

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.

#### Downloads:

#### Reverse dependencies:

Reverse depends: |
onlinePCA, SmartSVA |

Reverse imports: |
bigstatsr, dtwclust, filling, fungible, fuser, Gmedian, knockoff, kpcalg, MatrixCorrelation, MFKnockoffs, miRNAss, NetworkDistance, pcadapt, quanteda, randnet, rARPACK, Rdimtools, SISIR, SuperPCA, textmineR, umap |

Reverse linking to: |
autoFRK, Gmedian |

Reverse suggests: |
dimRed, recipes |

#### Linking:

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