SparseLSMR(_:)
Returns a least squares minimum residual method with specified options.
Declaration
func SparseLSMR(_ options: SparseLSMROptions) -> SparseIterativeMethodParameters
- options:
The LSMR options to use when creating the LSMR method.
Return Value
A SparseIterativeMethod structure that represents a default LSMR method.
Discussion
LSMR is a minimal residual (MINRES) method for solving least squares. Use LSMR to solve equations of the form Ax = b where an exact solution doesn’t exist. The returned solution minimizes ‖ b-Ax ‖₂.
Although LSMR is equivalent to applying MINRES to the normal equations AᵀAx = Aᵀb in exact arithmetic, it has superior numerical behavior and is the preferred method. Due to the implicit squaring of the condition of A in the normal equations, LSMR may struggle to converge in single precision. Use double-precision arithmetic where possible.
For symmetric positive-definite systems, use SparseConjugateGradient(_:). For square, full-rank unsymmetric or indefinite equations, use SparseGMRES(_:).