VivianePhilipps/marqLevAlgParallel: 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, 2021 <doi:10.32614/RJ-2021-089>.

Getting started

Package details

AuthorViviane Philipps, Cecile Proust-Lima, Melanie Prague, Boris Hejblum, Daniel Commenges, Amadou Diakite
MaintainerViviane Philipps <viviane.philipps@u-bordeaux.fr>
LicenseGPL (>= 2.0)
Version2.0.8
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("VivianePhilipps/marqLevAlgParallel")
VivianePhilipps/marqLevAlgParallel documentation built on Oct. 18, 2023, 2:16 p.m.