Package: gbm.auto
Title: Automated Boosted Regression Tree Modelling and Mapping Suite
Version: 2023.08.31
Authors@R: person("Simon", "Dedman", , "simondedman@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9108-972X"))
Description: 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 <http://www.simondedman.com/> for published guides and papers
    using this package.
License: MIT + file LICENSE
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)
Encoding: UTF-8
Language: en-GB
LazyData: true
RoxygenNote: 7.2.3
NeedsCompilation: no
Packaged: 2023-09-01 16:02:00 UTC; simon
Author: Simon Dedman [aut, cre] (<https://orcid.org/0000-0002-9108-972X>)
Maintainer: Simon Dedman <simondedman@gmail.com>
Repository: CRAN
Date/Publication: 2023-09-01 17:00:03 UTC
Built: R 4.2.3; ; 2024-04-24 02:54:15 UTC; windows
