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An R interface to nonlinear least-squares optimization with the GNU Scientific Library (GSL), see M. Galassi et al. (2009, ISBN:0954612078). The available trust region methods include the Levenberg-Marquardt algorithm with and without geodesic acceleration, the Steihaug-Toint conjugate gradient algorithm for large systems and several variants of Powell's dogleg algorithm. Multi-start optimization based on quasi-random samples is implemented using a modified version of the algorithm in Hickernell and Yuan (1997, OR Transactions). Bindings are provided to tune a number of parameters affecting the low-level aspects of the trust region algorithms. The interface mimics R's nls() function and returns model objects inheriting from the same class.
| Version: | 1.3.2 |
| Depends: | R (≥ 3.5) |
| Imports: | stats, Matrix |
| Published: | 2024-05-01 |
| Author: | Joris Chau [aut, cre] |
| Maintainer: | Joris Chau <joris.chau at openanalytics.eu> |
| BugReports: | https://github.com/JorisChau/gslnls/issues |
| License: | LGPL-3 |
| URL: | https://github.com/JorisChau/gslnls |
| NeedsCompilation: | yes |
| SystemRequirements: | GSL (>= 2.2) |
| Language: | en-US |
| Materials: | NEWS |
| In views: | Optimization |
| CRAN checks: | gslnls results |
| Reference manual: | gslnls.pdf |
| Package source: | gslnls_1.3.2.tar.gz |
| Windows binaries: | r-devel: gslnls_1.3.0.zip, r-release: gslnls_1.3.0.zip, r-oldrel: gslnls_1.3.0.zip |
| macOS binaries: | r-release (arm64): gslnls_1.3.2.tgz, r-oldrel (arm64): gslnls_1.3.2.tgz, r-release (x86_64): gslnls_1.3.2.tgz, r-oldrel (x86_64): gslnls_1.3.2.tgz |
| Old sources: | gslnls archive |
| Reverse imports: | germinationmetrics |
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