GSL Multi-Start Nonlinear Least-Squares Fitting
Overview
An R interface to weighted 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). Robust nonlinear regression can be performed using various robust loss functions, in which case the optimization problem is solved by iterative reweighted least squares (IRLS). 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.
confint(),summary()and other methods no longer fail in case of a singular gradient- Fixed bug: missing confidence/prediction intervals in
predict()for multi-startgsl_nls()call withfndefined as a function in combination withnewdata.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 24
- Examples that run
- 100%23 run in a plain check
- Exported functions with examples
- 86%
- Documented parameters
- 92%
- Return-value docs
- 100%
- Help pages citing references
- 25%
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- 61
- Median days to close, 50 most recently updated closed PRs
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6 development-tooling and community-health practices detected across 4 families in the upstream repository
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Dependencies
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- RR 4.6.0 released · 2026-04-24
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- 1.0.02021-10-07
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Package metadata
- First published
- 2021-10-07
- Total releases
- 12 / 5 yrs
- License
- LGPL-3 OSI · relicensed from GPL-3 in 1.2.0
- Minimum R
- ≥ 3.5
- Download size
- 152 KB
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