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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 optimization algorithms are Gauss-Newton, Levenberg-Marquardt, and the port library for bounded optimization. The package also provides tools to assist in simulation work using Emax regression.

Version: 0.1.1
Depends: R (≥ 3.5)
Imports: Deriv, minpack.lm, mvtnorm, rlang, stats, tibble, utils
Suggests: spelling, testthat (≥ 3.0.0)
Published: 2026-06-30
DOI: 10.32614/CRAN.package.emaxnls
Author: Danielle Navarro ORCID iD [aut, cre, cph]
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-US
Materials: README, NEWS
CRAN checks: emaxnls results

Documentation:

Reference manual: emaxnls.html , emaxnls.pdf

Downloads:

Package source: emaxnls_0.1.1.tar.gz
Windows binaries: r-devel: emaxnls_0.1.1.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_0.1.1.tgz, r-release (x86_64): emaxnls_0.1.1.tgz, r-oldrel (x86_64): emaxnls_0.1.1.tgz

Linking:

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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.