Iterative Solvers for (Sparse) Linear System of Equations
Generate a 2-dimensional discrete Poisson matrix
Gauss-Seidel method
Jacobi method
Successive Over-Relaxation method
Symmetric Successive Over-Relaxation method
Biconjugate Gradient method
Biconjugate Gradient Stabilized Method
Conjugate Gradient method
Conjugate Gradient Squared method
Chebyshev Method
Generalized Minimal Residual method
Quasi Minimal Residual Method
A Collection of Iterative Solvers for (Sparse) Linear System of Equati...
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>.