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flexFitR: Flexible Non-Linear Least Square Model Fitting

Provides tools for flexible non-linear least squares model fitting using general-purpose optimization techniques. The package supports a variety of optimization algorithms, including those provided by the 'optimx' package, making it suitable for handling complex non-linear models. Features include parallel processing support via the 'future' and 'foreach' packages, comprehensive model diagnostics, and visualization capabilities. Implements methods described in Nash and Varadhan (2011, <doi:10.18637/jss.v043.i09>).

Version: 1.0.0
Depends: R (≥ 2.10)
Imports: agriutilities, doFuture, dplyr, foreach, future, ggplot2, numDeriv, optimx, progressr, rlang, subplex, tibble, tidyr
Suggests: BB, dfoptim, ggpubr, kableExtra, knitr, lbfgsb3c, marqLevAlg, purrr, rmarkdown, ucminf
Published: 2025-01-20
DOI: 10.32614/CRAN.package.flexFitR
Author: Johan Aparicio [cre, aut], Jeffrey Endelman [aut], University of Wisconsin Madison [cph]
Maintainer: Johan Aparicio <aparicioarce at wisc.edu>
BugReports: https://github.com/AparicioJohan/flexFitR/issues
License: MIT + file LICENSE
URL: https://apariciojohan.github.io/flexFitR/, https://github.com/AparicioJohan/flexFitR
NeedsCompilation: no
Materials: README NEWS
CRAN checks: flexFitR results

Documentation:

Reference manual: flexFitR.pdf
Vignettes: Modeling (source, R code)
How to start (source, R code)
Modeling with constraints (source, R code)
Plotting options (source, R code)
Predicted values (source, R code)

Downloads:

Package source: flexFitR_1.0.0.tar.gz
Windows binaries: r-devel: flexFitR_1.0.0.zip, r-release: flexFitR_1.0.0.zip, r-oldrel: flexFitR_1.0.0.zip
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): flexFitR_1.0.0.tgz, r-oldrel (x86_64): not available

Linking:

Please use the canonical form https://CRAN.R-project.org/package=flexFitR 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.