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.
| Version: | 1.2.1 |
| Imports: | Rcpp (≥ 0.11.2) |
| LinkingTo: | Rcpp |
| Published: | 2014-08-31 |
| Author: | Antonio Coppola [aut, cre, cph], Brandon Stewart [aut, cph], Naoaki Okazaki [aut, cph], David Ardia [ctb, cph], Dirk Eddelbuettel [ctb, cph], Katharine Mullen [ctb, cph], Jorge Nocedal [ctb, cph] |
| Maintainer: | Antonio Coppola <acoppola at college.harvard.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| Materials: | README |
| In views: | Optimization |
| CRAN checks: | lbfgs results |
| Reference manual: | lbfgs.pdf |
| Vignettes: |
An R Package for Limited-memory BFGS Optimization |
| Package source: | lbfgs_1.2.1.tar.gz |
| Windows binaries: | r-devel: lbfgs_1.2.1.zip, r-release: lbfgs_1.2.1.zip, r-oldrel: lbfgs_1.2.1.zip |
| macOS binaries: | r-release: lbfgs_1.2.1.tgz, r-oldrel: lbfgs_1.2.1.tgz |
| Reverse imports: | GauPro, LUCIDus, splitfngr |
| Reverse suggests: | nlmixr, optimx, PlackettLuce, regsem, ROI.plugin.optimx, xtune |
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