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:
gslnls_1.3.3.tar.gz
gslnls_1.3.3.zip(r-4.5)gslnls_1.3.3.zip(r-4.4)gslnls_1.3.3.zip(r-4.3)
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)
gslnls_1.3.3.tgz(r-4.4-emscripten)gslnls_1.3.3.tgz(r-4.3-emscripten)
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')) |
Bug tracker:https://github.com/jorischau/gslnls/issues
gnu-scientific-librarygsllevenberg-marquardtmulti-startnonlinear-least-squaresnonlinear-regression
Last updated 6 months agofrom:3df1e460ec. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 05 2024 |
R-4.5-win-x86_64 | OK | Nov 05 2024 |
R-4.5-linux-x86_64 | OK | Nov 05 2024 |
R-4.4-win-x86_64 | OK | Nov 05 2024 |
R-4.4-mac-x86_64 | OK | Nov 05 2024 |
R-4.4-mac-aarch64 | OK | Nov 05 2024 |
R-4.3-win-x86_64 | OK | Nov 05 2024 |
R-4.3-mac-x86_64 | OK | Nov 05 2024 |
R-4.3-mac-aarch64 | OK | Nov 05 2024 |
Exports:confintdgsl_nlsgsl_nls_controlgsl_nls_largenls_test_listnls_test_problem