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A suite of tools to mitigate sampling bias in species occurrence records by thinning data in the environmental space (E-space). This process can improve the accuracy and precision of species distribution models (SDM, also known as ecological niche models, ENM). The package offers a data-driven protocol to determine thinning parameters using kernel-density bandwidth selection. Two thinning methods are provided (stochastic and deterministic) to reduce over-sampled environmental conditions and down-weight outlier observations. The name 'bean' reflects the core principle of the method: each 'pod' (a grid cell in E-space) is allowed to contain only a limited number of 'beans' (occurrence points). See Silverman (1986, ISBN:978-0-412-24620-3) and Rousseeuw and Leroy (2003, ISBN:978-0-471-48855-2) for the underlying statistical methods.
| Version: | 0.2.0 |
| Depends: | R (≥ 4.0) |
| Imports: | MASS, stats, terra |
| Suggests: | covr, knitr, rmarkdown, testthat (≥ 3.0.0), ggplot2, rgl |
| Published: | 2026-05-30 |
| DOI: | 10.32614/CRAN.package.bean |
| Author: | Paanwaris Paansri |
| Maintainer: | Paanwaris Paansri <paanwaris at vt.edu> |
| BugReports: | https://github.com/paanwaris/bean/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/paanwaris/bean, https://paanwaris.github.io/bean/ |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | bean results |
| Reference manual: | bean.html , bean.pdf |
| Vignettes: |
bean: an overview (source, R code) 1. Data preparation (source, R code) 2. Environmental thinning (source, R code) 3. Niche modeling (source, R code) |
| Package source: | bean_0.2.0.tar.gz |
| Windows binaries: | r-devel: bean_0.2.0.zip, r-release: not available, r-oldrel: bean_0.2.0.zip |
| macOS binaries: | r-release (arm64): bean_0.2.0.tgz, r-oldrel (arm64): bean_0.2.0.tgz, r-release (x86_64): bean_0.2.0.tgz, r-oldrel (x86_64): bean_0.2.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.