Header

UZH-Logo

Maintenance Infos

optimParallel: an R package providing a parallel version of the L-BFGS-B optimization method


Gerber, Florian; Furrer, Reinhard (2019). optimParallel: an R package providing a parallel version of the L-BFGS-B optimization method. R Journal, 11(1):352-358.

Abstract

The R package optimParallel provides a parallel version of the L-BFGS-B optimization method of optim(). The main function of the package is optimParallel(), which has the same usage and output as optim(). Using optimParallel() can significantly reduce the optimization time, especially when the evaluation time of the objective function is large and no analytical gradient is available. We introduce the R package and illustrate its implementation, which takes advantage of the lexical scoping mechanism of R.

Abstract

The R package optimParallel provides a parallel version of the L-BFGS-B optimization method of optim(). The main function of the package is optimParallel(), which has the same usage and output as optim(). Using optimParallel() can significantly reduce the optimization time, especially when the evaluation time of the objective function is large and no analytical gradient is available. We introduce the R package and illustrate its implementation, which takes advantage of the lexical scoping mechanism of R.

Statistics

Citations

Dimensions.ai Metrics
13 citations in Web of Science®
14 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

89 downloads since deposited on 16 Dec 2019
29 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Mathematics
Dewey Decimal Classification:510 Mathematics
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Physical Sciences > Numerical Analysis
Social Sciences & Humanities > Statistics, Probability and Uncertainty
Uncontrolled Keywords:Statistics, Probability and Uncertainty, Statistics and Probability, Numerical Analysis
Language:English
Date:1 January 2019
Deposited On:16 Dec 2019 09:11
Last Modified:07 Dec 2023 08:10
Publisher:R Foundation for Statistical Computing
ISSN:2073-4859
Additional Information:Creative Commons Attribution 4.0 International license
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.32614/rj-2019-030
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)