Package: nlsr 2025.02.16

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.

Authors:John C Nash [aut, cre], Duncan Murdoch [aut], Fernando Miguez [ctb], Arkajyoti Bhattacharjee [ctb]

nlsr_2025.02.16.tar.gz
nlsr_2025.02.16.zip(r-4.7)nlsr_2025.02.16.zip(r-4.6)nlsr_2025.02.16.zip(r-4.5)
nlsr_2025.02.16.tgz(r-4.6-any)nlsr_2025.02.16.tgz(r-4.5-any)
nlsr_2025.02.16.tar.gz(r-4.7-any)nlsr_2025.02.16.tar.gz(r-4.6-any)
nlsr_2025.02.16.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
nlsr/json (API)
NEWS

# Install 'nlsr' in R:
install.packages('nlsr', repos = c('https://nashjc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nashjc/nlsr/issues

On CRAN:

Conda:

6.60 score 1 stars 5 packages 105 scripts 815 downloads 1 mentions 39 exports 1 dependencies

Last updated from:7e4c212ee7. Checks:7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64WARNING126
source / vignettesOK223
linux-release-x86_64WARNING118
macos-release-arm64WARNING89
macos-oldrel-arm64WARNING100
windows-develWARNING91
windows-releaseWARNING74
windows-oldrelWARNING84
wasm-releaseOK110

Exports:codeDerivdexfindSubexprsfnDerivisCALLisMINUSONEisONEisZEROjabackjacentraljafwdjandmodel2rjfunmodel2ssgrfunmodelexprnewDerivnewSimplificationnlfbnlsDerivnlsrnlsr.controlnlsrSSnlsSimplifynlxbnumericDerivRnvecpctrlpnlspnlslmprtpshortrawresresgrresssSSlogisJNSSmod2rjfunsysDerivssysSimplificationswrapnlsr

Dependencies:digest

nlsr/nlsr Background, Development, and Discussion

John C. Nash

Rendered fromnlsr-devdoc.Rmdusingknitr::rmarkdownon May 17 2026.

Last update: 2024-04-06
Started: 2023-09-03

nlsr and Other Approaches to Derivatives in R

John C. Nash

Rendered fromnlsr-derivs.Rmdusingknitr::rmarkdownon May 17 2026.

Last update: 2024-04-06
Started: 2023-09-03

An introduction to nlsr

John C. Nash

Rendered fromIntro-to-nlsr.Rmdusingknitr::rmarkdownon May 17 2026.

Last update: 2024-04-06
Started: 2023-09-03

Specifying and Using Fixed Parameters in Nonlinear Estimation

John C. Nash

Rendered fromFixedParameters.Rmdusingknitr::rmarkdownon May 17 2026.

Last update: 2024-04-06
Started: 2023-09-03

Symbolic and analytical derivatives in R

John C. Nash

Rendered fromR-analytic-derivatives.Rmdusingknitr::rmarkdownon May 17 2026.

Last update: 2024-04-06
Started: 2023-09-03