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marqLevAlg
View on CRAN: Click
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Download and install marqLevAlg package within the R console
Install from CRAN:
install.packages("marqLevAlg")
Install from Github:
library("remotes")
install_github("cran/marqLevAlg")
Install by package version:
library("remotes")
install_version("marqLevAlg", "2.0.8")
Attach the package and use:
library("marqLevAlg")
Maintained by
Viviane Philipps
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-05-10
Latest Update: 2023-03-22
Description:
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 .
How to cite:
Viviane Philipps (2012). marqLevAlg: A Parallelized General-Purpose Optimization Based on Marquardt-Levenberg Algorithm. R package version 2.0.8, https://cran.r-project.org/web/packages/marqLevAlg
Previous versions and publish date:
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imports, suggests or enhances
Functions, R codes and Examples using
the marqLevAlg R package
Some associated functions: dataEx . deriva . deriva_grad . gradLMM . loglikLMM . marqLevAlg-package . marqLevAlg . print.marqLevAlg . summary.marqLevAlg .
Some associated R codes: dataEx.R . deriva.R . deriva_grad.R . exemple.R . func.R . func1.R . ghg.R . marqLevAlg-package.R . marqLevAlg.R . print.marqLevAlg.R . searpas.R . summary.marqLevAlg.R . sup.R . valfpa.R . Full marqLevAlg package functions and examples
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