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

Version:	2.0.7
Depends:	R (≥ 3.5.0)
Imports:	doParallel, foreach
Suggests:	microbenchmark, knitr, rmarkdown, ggplot2, viridis, patchwork, xtable
Published:	2022-07-08
Author:	Viviane Philipps, Cecile Proust-Lima, Melanie Prague, Boris Hejblum, Daniel Commenges, Amadou Diakite
Maintainer:	Viviane Philipps <viviane.philipps at u-bordeaux.fr>
BugReports:	https://github.com/VivianePhilipps/marqLevAlgParallel/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
NeedsCompilation:	yes
In views:	Optimization
CRAN checks:	marqLevAlg results

Documentation:

Reference manual:	marqLevAlg.pdf
Vignettes:	MLA

Downloads:

Package source:	marqLevAlg_2.0.7.tar.gz
Windows binaries:	r-devel: marqLevAlg_2.0.7.zip, r-release: marqLevAlg_2.0.7.zip, r-oldrel: marqLevAlg_2.0.7.zip
macOS binaries:	r-release (arm64): marqLevAlg_2.0.7.tgz, r-oldrel (arm64): marqLevAlg_2.0.7.tgz, r-release (x86_64): marqLevAlg_2.0.7.tgz, r-oldrel (x86_64): marqLevAlg_2.0.7.tgz
Old sources:	marqLevAlg archive

Reverse dependencies:

Reverse depends:	JLPM, lcmm
Reverse imports:	sfaR

Linking:

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