How to Install and Uninstall r-cran-rspectra Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: November 07,2024

1. Install "r-cran-rspectra" package

This guide let you learn how to install r-cran-rspectra on Ubuntu 20.10 (Groovy Gorilla)

$ sudo apt update $ sudo apt install r-cran-rspectra

2. Uninstall "r-cran-rspectra" package

Here is a brief guide to show you how to uninstall r-cran-rspectra on Ubuntu 20.10 (Groovy Gorilla):

$ sudo apt remove r-cran-rspectra $ sudo apt autoclean && sudo apt autoremove

3. Information about the r-cran-rspectra package on Ubuntu 20.10 (Groovy Gorilla)

Package: r-cran-rspectra
Architecture: amd64
Version: 0.16-0-1build2
Priority: optional
Section: universe/gnu-r
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian R Packages Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 1462
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-matrix (>= 1.1-0), r-cran-rcpp (>= 0.11.5), r-cran-rcppeigen (>= 0.3.3.3.0), libblas3 | libblas.so.3, libc6 (>= 2.14), libgcc-s1 (>= 4.0), liblapack3 | liblapack.so.3, libstdc++6 (>= 9)
Suggests: r-cran-knitr, r-cran-rmarkdown
Filename: pool/universe/r/r-cran-rspectra/r-cran-rspectra_0.16-0-1build2_amd64.deb
Size: 397408
MD5sum: 20630711588a64c8e200ea63dab0bce8
SHA1: b870150c913e497a5075306353886e63ef7eefac
SHA256: 9af454eabe0b845705ea29e6d61275bdd0dbf01721983f17ddf5a5d1a193b5f8
SHA512: ac7623112307f2be5016b96eed018888802ece48bf1aec3d6804d2b10cb9cbe3a30dbd3b8ce75e1fec7a071359e984c7e07943fd9633652dcce7e601eb437761
Homepage: https://cran.r-project.org/package=RSpectra
Description-en: GNU R solvers for large-scale eigenvalue and SVD problems
This package provides a 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.
Description-md5: 97910890d8dc98a5be85efc79d7767c5