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: | 2019.9.7 |
Depends: | R (≥ 3.0) |
Imports: | digest |
Suggests: | minpack.lm, optimx, Rvmmin, Rcgmin, numDeriv, knitr, rmarkdown, Ryacas, Deriv |
Published: | 2019-09-08 |
Author: | John C Nash [aut, cre], Duncan Murdoch [aut] |
Maintainer: | John C Nash <nashjc at uottawa.ca> |
License: | GPL-2 |
NeedsCompilation: | no |
Materials: | NEWS |
In views: | Optimization |
CRAN checks: | nlsr results |
Reference manual: | nlsr.pdf |
Vignettes: |
Specifying Fixed Parameters nlsr Derivatives nlsr Background, Development, Examples and Discussion |
Package source: | nlsr_2019.9.7.tar.gz |
Windows binaries: | r-devel: nlsr_2019.9.7.zip, r-release: nlsr_2019.9.7.zip, r-oldrel: nlsr_2019.9.7.zip |
macOS binaries: | r-release: nlsr_2019.9.7.tgz, r-oldrel: nlsr_2019.9.7.tgz |
Old sources: | nlsr archive |
Reverse depends: | colf |
Reverse imports: | usl |
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