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.
- Version2.0.8
- R version≥ 3.5.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release03/22/2023
Documentation
Team
Viviane Philipps
Melanie Prague
Boris Hejblum
Cecile Proust-Lima
Amadou Diakite
Daniel Commenges
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