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Fast routines for solving large systems of linear equations in R. Makes Eigen Cholesky-, LU-, QR-, and iterative (Conjugate Gradient, BiCGSTAB) solvers for both dense and sparse problems available.

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README.md

sanic: Solving Ax = b Nimbly in C++

Routines for solving large systems of linear equations in R. Direct and iterative solvers from the Eigen C++ library are made available. Solvers include Cholesky, LU, QR, and Krylov subspace methods (Conjugate Gradient, BiCGSTAB). Both dense and sparse problems are supported.

Solvers

Solver Notes Sparse method Reference
LU decomposition Partial pivoting, blocking Yes 1, 2
Householder QR decomposition Column pivoting, good reliability Yes 1, 2, 3
Cholesky decomposition Semidefinite symmetric problems, pivoting Yes 1, 2
Conjugate Gradient (CG) Symmetric problems, Jacobi preconditioner Always 1
Least Squares (LS) CG Rectangular LS problems, LS Jacobi preconditioner Always 1
Biconjugate gradient stabilised Square problems, Jacobi preconditioner Always 1

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Fast routines for solving large systems of linear equations in R. Makes Eigen Cholesky-, LU-, QR-, and iterative (Conjugate Gradient, BiCGSTAB) solvers for both dense and sparse problems available.

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