lbfgs swMATH ID: 26415 Software Authors: Antonio Coppola, Brandon Stewart, Naoaki Okazaki, David Ardia, Dirk Eddelbuettel, Katharine Mullen, Jorge Noceda Description: R package lbfgs: Limited-memory BFGS Optimization. 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. Homepage: https://cran.r-project.org/web/packages/lbfgs/index.html Source Code: https://github.com/cran/lbfgs Dependencies: R Related Software: choix; hyper2; mixedMem; PlackettLuce; PLMIX; Pmr; gnm; PrefLib; ROlogit; CRAN; rankdist; Rankcluster; PerMallows; psychotree; prefmod; igraph; R Cited in: 1 Publication Cited by 4 Authors 1 Firth, David 1 Kosmidis, Ioannis 1 Turner, Heather L. 1 van Etten, Jacob Cited in 1 Serial 1 Computational Statistics Cited in 1 Field 1 Numerical analysis (65-XX) Citations by Year