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 and 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: 1.0.0
Depends: R (≥ 3.5)
Imports: ggplot2 (≥ 2.2.0), brnn (≥ 0.6), mgcv (≥ 1.8-34), knitr (≥ 1.19), dplyr (≥ 0.1.0), magrittr (≥ 1.5)
Suggests: testthat (≥ 3.0.0)
Published: 2022-02-19
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


Reference manual: rTG.pdf


Package source: rTG_1.0.0.tar.gz
Windows binaries: r-devel: rTG_1.0.0.zip, r-release: rTG_1.0.0.zip, r-oldrel: rTG_1.0.0.zip
macOS binaries: r-release (arm64): rTG_1.0.0.tgz, r-release (x86_64): rTG_1.0.0.tgz, r-oldrel: rTG_1.0.0.tgz
Old sources: rTG archive


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