nlsr: Functions for Nonlinear Least Squares Solutions - Updated 2022 (original) (raw)
Provides tools for working with nonlinear least squares problems. For the estimation of models reliable and robust tools than nls(), where the the Gauss-Newton method frequently stops with 'singular gradient' messages. This is accomplished by using, where possible, analytic derivatives to compute the matrix of derivatives and a stabilization of the solution of the estimation equations. Tools for approximate or externally supplied derivative matrices are included. Bounds and masks on parameters are handled properly.
| Version: | 2023.8.31 |
|---|---|
| Depends: | R (≥ 3.5) |
| Imports: | digest |
| Suggests: | minpack.lm, optimx, numDeriv, knitr, rmarkdown, markdown, Ryacas, Deriv, microbenchmark, MASS, ggplot2, nlraa |
| Published: | 2023-09-05 |
| DOI: | 10.32614/CRAN.package.nlsr |
| Author: | John C Nash [aut, cre], Duncan Murdoch [aut], Fernando Miguez [ctb], Arkajyoti Bhattacharjee [ctb] |
| Maintainer: | John C Nash |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Materials: | README |
| In views: | Optimization |
| CRAN checks: | nlsr results |
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