Provides tools for working with nonlinear least squares problems. It is intended to eventually supersede the nls() function in the R distribution. For example, nls() specifically does NOT deal with small or zero residual problems as its Gauss-Newton method frequently stops with 'singular gradient' messages. nlsr is based on the now-deprecated package nlmrt, and has refactored functions and R-language symbolic derivative features.
| Version: | 2017.10.4 |
| Depends: | R (≥ 3.0) |
| Imports: | digest |
| Suggests: | minpack.lm, optimr, Rvmmin, Rcgmin, numDeriv, knitr, rmarkdown, Ryacas, Deriv |
| Published: | 2017-10-05 |
| Author: | John C Nash [aut, cre], Duncan Murdoch [aut] |
| Maintainer: | John C Nash <nashjc at uottawa.ca> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | nlsr results |
| Reference manual: | nlsr.pdf |
| Vignettes: |
Specifying Fixed Parameters nlsr Derivatives nlsr Background, Development, Examples and Discussion |
| Package source: | nlsr_2017.10.4.tar.gz |
| Windows binaries: | r-devel: nlsr_2017.10.4.zip, r-release: nlsr_2017.10.4.zip, r-oldrel: nlsr_2017.10.4.zip |
| OS X El Capitan binaries: | r-release: nlsr_2017.10.4.tgz |
| OS X Mavericks binaries: | r-oldrel: nlsr_2017.10.4.tgz |
| Old sources: | nlsr archive |
| Reverse depends: | colf |
| Reverse imports: | usl |
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