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
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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