eSDM: Ensemble Tool for Predictions from Species Distribution Models

A tool which allows users to create and evaluate ensembles of species distribution model (SDM) predictions. Functionality is offered through R functions or a GUI (R Shiny app). This tool can assist users in identifying spatial uncertainties and making informed conservation and management decisions. The package is further described in Woodman et al (2019) <doi:10.1111/2041-210X.13283>.

Version: 0.3.3
Depends: R (≥ 3.5.0)
Imports: dplyr (≥ 0.7-0), magrittr, methods, purrr, rlang, ROCR, sf (≥ 0.9-0), shiny, stats, units
Suggests: colorRamps, colourpicker, dichromat, DT, knitr, leafem, leaflet, maps, maptools, raster, RColorBrewer, rmarkdown, shinybusy, shinydashboard, shinyjs, testthat (≥ 2.1.0), tmap (≥ 2.3), viridis, zip
Published: 2020-04-15
Author: Sam Woodman ORCID iD [aut, cre]
Maintainer: Sam Woodman <sam.woodman at noaa.gov>
BugReports: https://github.com/smwoodman/eSDM/issues
License: GPL-3
URL: https://smwoodman.github.io/eSDM, https://github.com/smwoodman/eSDM
NeedsCompilation: no
Citation: eSDM citation info
Materials: NEWS
CRAN checks: eSDM results

Downloads:

Reference manual: eSDM.pdf
Vignettes: Example analysis - Woodman et al 2019
Package source: eSDM_0.3.3.tar.gz
Windows binaries: r-prerelease: eSDM_0.3.3.zip, r-release: eSDM_0.3.3.zip, r-oldrel: eSDM_0.3.3.zip
macOS binaries: r-prerelease: eSDM_0.3.2.tgz, r-release: eSDM_0.3.3.tgz, r-oldrel: eSDM_0.3.2.tgz
Old sources: eSDM archive

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