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lbfgs  

Limited-memory BFGS Optimization
View on CRAN: Click here


Download and install lbfgs package within the R console
Install from CRAN:
install.packages("lbfgs")

Install from Github:
library("remotes")
install_github("cran/lbfgs")

Install by package version:
library("remotes")
install_version("lbfgs", "1.2.1.2")



Attach the package and use:
library("lbfgs")
Maintained by
Antonio Coppola
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-08-31
Latest Update: 2022-06-23
Description:
A wrapper built around the libLBFGS optimization library by Naoaki Okazaki. The lbfgs package implements both the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) and the Orthant-Wise Quasi-Newton Limited-Memory (OWL-QN) optimization algorithms. The L-BFGS algorithm solves the problem of minimizing an objective, given its gradient, by iteratively computing approximations of the inverse Hessian matrix. The OWL-QN algorithm finds the optimum of an objective plus the L1-norm of the problem's parameters. The package offers a fast and memory-efficient implementation of these optimization routines, which is particularly suited for high-dimensional problems.
How to cite:
Antonio Coppola (2014). lbfgs: Limited-memory BFGS Optimization. R package version 1.2.1.2, https://cran.r-project.org/web/packages/lbfgs. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.2.1.1 (2022-05-23 10:27), 1.2.1 (2014-08-31 11:23)
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Other R packages that lbfgs depends, imports, suggests or enhances
Complete documentation for lbfgs
Functions, R codes and Examples using the lbfgs R package
Some associated functions: Leukemia . lbfgs . 
Some associated R codes: lbfgs.R .  Full lbfgs package functions and examples
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