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, GaussSeidel, Successive OverRelaxation 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>.
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License  GPL (>= 3) 
Version  0.4.0 
Package repository  View on GitHub 
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