SparseLSMROptions
Options for creating a least squares minimum residual method.
Declaration
struct SparseLSMROptionsOverview
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 A__ᵀ__Ax = A__ᵀ__b 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(_:).
Topics
Initializers
init()init(reportError:lambda:nvec:convergenceTest:atol:rtol:btol:conditionLimit:maxIterations:reportStatus:)