Package: rTG 1.0.3

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().

Authors:Jernej Jevsenak [aut, cre]

rTG_1.0.3.tar.gz
rTG_1.0.3.zip(r-4.5)rTG_1.0.3.zip(r-4.4)rTG_1.0.3.zip(r-4.3)
rTG_1.0.3.tgz(r-4.4-any)rTG_1.0.3.tgz(r-4.3-any)
rTG_1.0.3.tar.gz(r-4.5-noble)rTG_1.0.3.tar.gz(r-4.4-noble)
rTG_1.0.3.tgz(r-4.4-emscripten)rTG_1.0.3.tgz(r-4.3-emscripten)
rTG.pdf |rTG.html
rTG/json (API)
NEWS

# Install 'rTG' in R:
install.packages('rTG', repos = c('https://jernejjevsenak.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/jernejjevsenak/rtg/issues

Datasets:

On CRAN:

3.00 score 1 stars 9 scripts 273 downloads 2 exports 40 dependencies

Last updated 4 months agofrom:74caf5baaa. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-winOKNov 22 2024
R-4.5-linuxOKNov 22 2024
R-4.4-winOKNov 22 2024
R-4.4-macOKNov 22 2024
R-4.3-winOKNov 22 2024
R-4.3-macOKNov 22 2024

Exports:double_gompertzXPSgrowth

Dependencies:brnnclicolorspacedplyrevaluatefansifarverFormulagenericsggplot2gluegtablehighrisobandknitrlabelinglatticelifecyclemagrittrMASSMatrixmgcvminpack.lmmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbletidyselecttruncnormutf8vctrsviridisLitewithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
data_dendrometersdata_dendrometers
data_treesdata_trees
parametersparameters
XPSgrowthXPSgrowth