emaxnls: Nonlinear Least Squares Estimation for Emax Regression Models

Provides estimation and covariate selection tools for Emax regression models using nonlinear least squares methods. Supported optimisation algorithms are Gauss-Newton, Levenberg-Marquardt, and the port library for bounded optimisation. The package also provides tools to assist in simulation work using Emax regression.

Version: 0.2.0
Depends: R (≥ 3.5)
Imports: Deriv, minpack.lm, mvtnorm, rlang, stats, utils
Suggests: erplots, spelling, testthat (≥ 3.0.0), tibble
Published: 2026-09-16
DOI: 10.32614/CRAN.package.emaxnls
Author: Danielle Navarro ORCID iD [aut, cre]
Maintainer: Danielle Navarro <djnavarro at protonmail.com>
BugReports: https://github.com/djnavarro/emaxnls/issues
License: MIT + file LICENSE
URL: https://github.com/djnavarro/emaxnls, https://emaxnls.djnavarro.net/
NeedsCompilation: no
Language: en-GB
Materials: README, NEWS
CRAN checks: emaxnls results

Documentation:

Reference manual: emaxnls.html , emaxnls.pdf

Downloads:

Package source: emaxnls_0.2.0.tar.gz
Windows binaries: r-devel: emaxnls_0.2.0.zip, r-release: emaxnls_0.1.1.zip, r-oldrel: emaxnls_0.1.1.zip
macOS binaries: r-release (arm64): emaxnls_0.1.1.tgz, r-oldrel (arm64): emaxnls_0.2.0.tgz, r-release (x86_64): emaxnls_0.2.0.tgz, r-oldrel (x86_64): emaxnls_0.2.0.tgz
Old sources: emaxnls archive

Linking:

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