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rTG: Methods to Analyse Seasonal Radial Tree Growth Data

Methods for comparing different regression algorithms for describing the temporal dynamics of secondary tree growth (xylem and phloem). Users can compare the accuracy of the most common fitting methods usually used to analyse xylem and phloem data, i.e., Gompertz function, Double Gompertz function, General Additive Models (GAMs); and an algorithm newly introduced to the field, i.e., Bayesian Regularised Neural Networks (brnn). The core function of the package is XPSgrowth(), while the results can be interpreted using implemented generic S3 methods, such as plot() and summary().

Version: 1.0.3
Depends: R (≥ 3.5), brnn (≥ 0.6), minpack.lm (≥ 1.2-4)
Imports: ggplot2 (≥ 2.2.0), mgcv (≥ 1.8-34), knitr (≥ 1.19), dplyr (≥ 0.1.0), magrittr (≥ 1.5), methods
Suggests: testthat (≥ 3.0.0)
Published: 2024-07-25
DOI: 10.32614/CRAN.package.rTG
Author: Jernej Jevsenak [aut, cre]
Maintainer: Jernej Jevsenak <jernej.jevsenak at gmail.com>
BugReports: https://github.com/jernejjevsenak/rTG/issues
License: GPL-3
URL: https://github.com/jernejjevsenak/rTG
NeedsCompilation: no
Citation: rTG citation info
Materials: NEWS
CRAN checks: rTG results

Documentation:

Reference manual: rTG.pdf

Downloads:

Package source: rTG_1.0.3.tar.gz
Windows binaries: r-devel: rTG_1.0.3.zip, r-release: rTG_1.0.3.zip, r-oldrel: rTG_1.0.3.zip
macOS binaries: r-release (arm64): rTG_1.0.3.tgz, r-oldrel (arm64): rTG_1.0.3.tgz, r-release (x86_64): rTG_1.0.3.tgz, r-oldrel (x86_64): rTG_1.0.3.tgz
Old sources: rTG archive

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.