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RSpectra
View on CRAN: Click
here
Download and install RSpectra package within the R console
Install from CRAN:
install.packages("RSpectra")
Install from Github:
library("remotes")
install_github("cran/RSpectra")
Install by package version:
library("remotes")
install_version("RSpectra", "0.16-2")
Attach the package and use:
library("RSpectra")
Maintained by
Yixuan Qiu
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-02-29
Latest Update: 2022-04-24
Description:
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.
How to cite:
Yixuan Qiu (2016). RSpectra: Solvers for Large-Scale Eigenvalue and SVD Problems. R package version 0.16-2, https://cran.r-project.org/web/packages/RSpectra. Accessed 18 Feb. 2025.
Previous versions and publish date:
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Other R packages that RSpectra depends,
imports, suggests or enhances
Complete documentation for RSpectra
Functions, R codes and Examples using
the RSpectra R package
Some associated functions: eigs . svds .
Some associated R codes: 00_eigs.R . 10_eigs_real_gen.R . 20_eigs_real_sym.R . 30_svds.R . 40_svds_real_gen.R . 50_svds_real_sym.R . 99_is_sym.R . Full RSpectra package functions and examples
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