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nlsr: Functions for Nonlinear Least Squares Solutions - Updated 2022

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 <nashjc at uottawa.ca>
License: GPL-2
NeedsCompilation: no
Materials: README NEWS
In views: Optimization
CRAN checks: nlsr results

Documentation:

Reference manual: nlsr.pdf
Vignettes: Specifying Fixed Parameters
nlsr Introduction
Symbolic and analytical derivatives in R
nlsr Derivatives
nlsr Background, Development, Examples and Discussion

Downloads:

Package source: nlsr_2023.8.31.tar.gz
Windows binaries: r-devel: nlsr_2023.8.31.zip, r-release: nlsr_2023.8.31.zip, r-oldrel: nlsr_2023.8.31.zip
macOS binaries: r-release (arm64): nlsr_2023.8.31.tgz, r-oldrel (arm64): nlsr_2023.8.31.tgz, r-release (x86_64): nlsr_2023.8.31.tgz, r-oldrel (x86_64): nlsr_2023.8.31.tgz
Old sources: nlsr archive

Reverse dependencies:

Reverse depends: colf
Reverse imports: beezdemand, genSEIR, usl

Linking:

Please use the canonical form https://CRAN.R-project.org/package=nlsr to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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