S4DM: Small Sample Size Species Distribution Modeling

Implements a set of distribution modeling methods that are suited to species with small sample sizes (e.g., poorly sampled species or rare species). While these methods can also be used on well-sampled taxa, they are united by the fact that they can be utilized with relatively few data points. More details on the currently implemented methodologies can be found in Drake and Richards (2018) <doi:10.1002/ecs2.2373>, Drake (2015) <doi:10.1098/rsif.2015.0086>, and Drake (2014) <doi:10.1890/ES13-00202.1>.

Version: 0.0.1
Depends: R (≥ 3.5.0)
Imports: corpcor, densratio, flexclust, geometry, kernlab, maxnet, mvtnorm, np, pROC, robust, rvinecopulib, sf, terra, dplyr, Rdpack
Suggests: geodata, BIEN, ggplot2, tidyterra, knitr, testthat, rmarkdown
Published: 2025-01-10
DOI: 10.32614/CRAN.package.S4DM
Author: Brian S. Maitner ORCID iD [aut, cre], Robert L. Richards [aut], Ben S. Carlson [aut], John M. Drake [aut], Cory Merow [aut]
Maintainer: Brian S. Maitner <bmaitner at usf.edu>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: S4DM results

Documentation:

Reference manual: S4DM.pdf
Vignettes: S4DM R package (source, R code)

Downloads:

Package source: S4DM_0.0.1.tar.gz
Windows binaries: r-devel: not available, r-release: S4DM_0.0.1.zip, r-oldrel: S4DM_0.0.1.zip
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): S4DM_0.0.1.tgz, r-oldrel (x86_64): S4DM_0.0.1.tgz

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