nlsr: Functions for Nonlinear Least Squares Solutions

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. Its Gauss-Newton method frequently stops with 'singular gradient' messages.

Version: 2017.6.18
Depends: R (≥ 3.0)
Imports: digest
Suggests: minpack.lm, optimr, Rvmmin, Rcgmin, numDeriv, knitr, rmarkdown, Ryacas, Deriv, nlmrt
Published: 2017-06-19
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

Downloads:

Reference manual: nlsr.pdf
Vignettes: Specifying Fixed Parameters
nlsr Derivatives
nlsr Background, Development, Examples and Discussion
Package source: nlsr_2017.6.18.tar.gz
Windows binaries: r-devel: nlsr_2017.6.18.zip, r-release: nlsr_2017.6.18.zip, r-oldrel: nlsr_2017.6.18.zip
OS X El Capitan binaries: r-release: nlsr_2017.2.19.tgz
OS X Mavericks binaries: r-oldrel: nlsr_2017.6.18.tgz
Old sources: nlsr archive

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