Package: nlmrt 2016.3.2

nlmrt: Functions for Nonlinear Least Squares Solutions

Replacement for nls() tools for working with nonlinear least squares problems. The calling structure is similar to, but much simpler than, that of the nls() function. Moreover, where nls() specifically does NOT deal with small or zero residual problems, nlmrt is quite happy to solve them. It also attempts to be more robust in finding solutions, thereby avoiding 'singular gradient' messages that arise in the Gauss-Newton method within nls(). The Marquardt-Nash approach in nlmrt generally works more reliably to get a solution, though this may be one of a set of possibilities, and may also be statistically unsatisfactory. Added print and summary as of August 28, 2012.

Authors:John C. Nash [aut, cre]

nlmrt_2016.3.2.tar.gz
nlmrt_2016.3.2.zip(r-4.5)nlmrt_2016.3.2.zip(r-4.4)nlmrt_2016.3.2.zip(r-4.3)
nlmrt_2016.3.2.tgz(r-4.4-any)nlmrt_2016.3.2.tgz(r-4.3-any)
nlmrt_2016.3.2.tar.gz(r-4.5-noble)nlmrt_2016.3.2.tar.gz(r-4.4-noble)
nlmrt_2016.3.2.tgz(r-4.4-emscripten)nlmrt_2016.3.2.tgz(r-4.3-emscripten)
nlmrt.pdf |nlmrt.html
nlmrt/json (API)
NEWS

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

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.69 score 49 scripts 263 downloads 9 exports 0 dependencies

Last updated 9 years agofrom:3803849a65. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 17 2024
R-4.5-winNOTEOct 17 2024
R-4.5-linuxNOTEOct 17 2024
R-4.4-winNOTEOct 17 2024
R-4.4-macNOTEOct 17 2024
R-4.3-winNOTEOct 17 2024
R-4.3-macNOTEOct 17 2024

Exports:model2grfunmodel2jacfunmodel2resfunmodel2ssfunmodgrmodssnlfbnlxbwrapnls

Dependencies:

nlmrt Tutorial

Rendered fromnlmrt-vignette.Rnwusingutils::Sweaveon Oct 17 2024.

Last update: 2016-03-04
Started: 2013-08-10