https://github.com/cran/lbfgs
Raw File
Tip revision: 2fb6e0258a7cd3592fc5c9de4ff8782a19d081f6 authored by Antonio Coppola on 23 June 2022, 11:40:02 UTC
version 1.2.1.2
Tip revision: 2fb6e02
DESCRIPTION
Package: lbfgs
Type: Package
Title: Limited-memory BFGS Optimization
Version: 1.2.1.2
Date: 2022-06-23
Authors@R: c(person("Antonio", "Coppola", role = c("aut", "cre", "cph"), email = "acoppola@stanford.edu"),
	      person("Brandon", "Stewart", role = c("aut", "cph")),
	      person("Naoaki", "Okazaki", role = c("aut", "cph")),
	      person("David", "Ardia", role = c("ctb", "cph")),
	      person("Dirk", "Eddelbuettel", role = c("ctb", "cph")),
	      person("Katharine", "Mullen", role = c("ctb", "cph")),
	      person("Jorge", "Nocedal", role = c("ctb", "cph")))
Maintainer: Antonio Coppola <acoppola@stanford.edu>
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.
License: GPL (>= 2)
Imports: Rcpp (>= 0.11.2), methods
LinkingTo: Rcpp
Packaged: 2022-06-23 10:39:41 UTC; acoppola
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]
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2022-06-23 12:40:02 UTC
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