marqLevAlg (version 2.0.8)
A Parallelized General-Purpose Optimization Based on
Marquardt-Levenberg Algorithm
Description
This algorithm provides a numerical solution to the
problem of unconstrained local minimization (or maximization). It is particularly suited for complex problems and more efficient than
the Gauss-Newton-like algorithm when starting from points very
far from the final minimum (or maximum). Each iteration is parallelized and convergence relies on a stringent stopping criterion based on the first and second derivatives. See Philipps et al, 2021 .