Automates delta log-normal boosted regression tree abundance prediction. Loops through parameters provided (LR (learning rate), TC (tree complexity), BF (bag fraction)), chooses best, simplifies, & generates line, dot & bar plots, & outputs these & predictions & a report, makes predicted abundance maps, and Unrepresentativeness surfaces. Package core built around 'gbm' (gradient boosting machine) functions in 'dismo' (Hijmans, Phillips, Leathwick & Jane Elith, 2020 & ongoing), itself built around 'gbm' (Greenwell, Boehmke, Cunningham & Metcalfe, 2020 & ongoing, originally by Ridgeway). Indebted to Elith/Leathwick/Hastie 2008 'Working Guide' <doi:10.1111/j.1365-2656.2008.01390.x>; workflow follows Appendix S3. See <https://www.simondedman.com/> for published guides and papers using this package.
Version: 2024.10.01 Depends: R (≥ 3.5.0) Imports: beepr (≥ 1.2), dismo (≥ 1.3-14), dplyr (≥ 1.0.9), gbm (≥ 2.1.1), ggmap (≥ 3.0.2), ggplot2 (≥ 3.4.2), ggspatial (≥ 1.1.9), lifecycle, lubridate (≥ 1.9.2), mapplots (≥ 1.5), Metrics (≥ 0.1.4), readr (≥ 2.1.4), sf (≥ 0.9-7), stars (≥ 0.6-3), starsExtra (≥ 0.2.7), stats (≥ 3.3.1), stringi (≥ 1.6.1), tidyselect (≥ 1.2.0), viridis (≥ 0.6.4) Published: 2024-10-01 DOI: 10.32614/CRAN.package.gbm.auto Author: Simon Dedman [aut, cre] Maintainer: Simon Dedman <simondedman at gmail.com> License: MIT + file LICENSE NeedsCompilation: no Language: en-GB Citation: gbm.auto citation info Materials: README, NEWS CRAN checks: gbm.auto results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=gbm.auto to link to this page.
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