pdi: Phenotypic Index Measures for Oak Decline Severity

Oak declines are complex disease syndromes and consist of many visual indicators that include aspects of tree size, crown condition and trunk condition. This can cause difficulty in the manual classification of symptomatic and non-symptomatic trees from what is in reality a broad spectrum of oak tree health condition. Two phenotypic oak decline indexes have been developed to quantitatively describe and differentiate oak decline syndromes in Quercus robur. This package provides a toolkit to generate these decline indexes from phenotypic descriptors using the machine learning algorithm random forest. The methodology for generating these indexes is outlined in Finch et al. (2121) <doi:10.1016/j.foreco.2021.118948>.

Version: 0.4.2
Imports: dplyr, magrittr, purrr, randomForest, readxl, stringr, tibble, tidyr, tidyselect
Suggests: testthat, covr, knitr, rmarkdown, ggplot2
Published: 2021-02-09
Author: Jasen Finch ORCID iD [aut, cre]
Maintainer: Jasen Finch <jsf9 at aber.ac.uk>
BugReports: https://github.com/jasenfinch/pdi/issues
License: GPL-3
URL: https://jasenfinch.github.io/pdi
NeedsCompilation: no
Materials: README NEWS
CRAN checks: pdi results


Reference manual: pdi.pdf
Vignettes: Generating phenotypic decline indexes using the pdi package
Package source: pdi_0.4.2.tar.gz
Windows binaries: r-devel: pdi_0.4.2.zip, r-release: pdi_0.4.2.zip, r-oldrel: pdi_0.4.2.zip
macOS binaries: r-release: pdi_0.4.2.tgz, r-oldrel: pdi_0.4.2.tgz
Old sources: pdi archive


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