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Rlinsolve: Iterative Solvers for (Sparse) Linear System of Equations

Solving a system of linear equations is one of the most fundamental computational problems for many fields of mathematical studies, such as regression problems from statistics or numerical partial differential equations. We provide basic stationary iterative solvers such as Jacobi, Gauss-Seidel, Successive Over-Relaxation and SSOR methods. Nonstationary, also known as Krylov subspace methods are also provided. Sparse matrix computation is also supported in that solving large and sparse linear systems can be manageable using 'Matrix' package along with 'RcppArmadillo'. For a more detailed description, see a book by Saad (2003) <doi:10.1137/1.9780898718003>.

Version: 0.3.2
Imports: Rcpp (≥ 0.12.4), Matrix, Rdpack, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Published: 2021-08-21
DOI: 10.32614/CRAN.package.Rlinsolve
Author: Kisung You ORCID iD [aut, cre]
Maintainer: Kisung You <kisungyou at outlook.com>
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: NEWS
In views: NumericalMathematics
CRAN checks: Rlinsolve results

Documentation:

Reference manual: Rlinsolve.pdf

Downloads:

Package source: Rlinsolve_0.3.2.tar.gz
Windows binaries: r-devel: Rlinsolve_0.3.2.zip, r-release: Rlinsolve_0.3.2.zip, r-oldrel: Rlinsolve_0.3.2.zip
macOS binaries: r-release (arm64): Rlinsolve_0.3.2.tgz, r-oldrel (arm64): Rlinsolve_0.3.2.tgz, r-release (x86_64): Rlinsolve_0.3.2.tgz, r-oldrel (x86_64): Rlinsolve_0.3.2.tgz
Old sources: Rlinsolve archive

Reverse dependencies:

Reverse imports: ZVCV

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.