Package: gslnls 1.3.3

gslnls: GSL Multi-Start Nonlinear Least-Squares Fitting

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.

Authors:Joris Chau [aut, cre]

gslnls_1.3.3.tar.gz
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gslnls_1.3.3.tgz(r-4.4-x86_64)gslnls_1.3.3.tgz(r-4.4-arm64)gslnls_1.3.3.tgz(r-4.3-x86_64)gslnls_1.3.3.tgz(r-4.3-arm64)
gslnls_1.3.3.tar.gz(r-4.5-noble)gslnls_1.3.3.tar.gz(r-4.4-noble)
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gslnls.pdf |gslnls.html
gslnls/json (API)
NEWS

# Install 'gslnls' in R:
install.packages('gslnls', repos = c('https://jorischau.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/jorischau/gslnls/issues

Uses libs:
  • gsl– GNU Scientific Library (GSL)
  • fortran– Runtime library for GNU Fortran applications

On CRAN:

gnu-scientific-librarygsllevenberg-marquardtmulti-startnonlinear-least-squaresnonlinear-regression

5.77 score 15 stars 1 packages 33 scripts 996 downloads 6 exports 2 dependencies

Last updated 6 months agofrom:3df1e460ec. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 05 2024
R-4.5-win-x86_64OKNov 05 2024
R-4.5-linux-x86_64OKNov 05 2024
R-4.4-win-x86_64OKNov 05 2024
R-4.4-mac-x86_64OKNov 05 2024
R-4.4-mac-aarch64OKNov 05 2024
R-4.3-win-x86_64OKNov 05 2024
R-4.3-mac-x86_64OKNov 05 2024
R-4.3-mac-aarch64OKNov 05 2024

Exports:confintdgsl_nlsgsl_nls_controlgsl_nls_largenls_test_listnls_test_problem

Dependencies:latticeMatrix