marqLevAlg: A Parallelized General-Purpose Optimization Based on Marquardt-Levenberg Algorithm

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, 2020 <arXiv:2009.03840>.

Getting started

Package details

AuthorViviane Philipps, Cecile Proust-Lima, Melanie Prague, Boris Hejblum, Daniel Commenges, Amadou Diakite
MaintainerViviane Philipps <>
LicenseGPL (>= 2.0)
Package repositoryView on CRAN
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marqLevAlg documentation built on April 2, 2021, 1:05 a.m.