hypervolume: High Dimensional Geometry, Set Operations, Projection, and Inference Using Kernel Density Estimation, Support Vector Machines, and Convex Hulls (original) (raw)
Estimates the shape and volume of high-dimensional datasets and performs set operations: intersection / overlap, union, unique components, inclusion test, and hole detection. Uses stochastic geometry approach to high-dimensional kernel density estimation, support vector machine delineation, and convex hull generation. Applications include modeling trait and niche hypervolumes and species distribution modeling.
| Version: | 3.1.6 |
|---|---|
| Depends: | Rcpp, methods, R (≥ 3.5.0) |
| Imports: | raster, maps, MASS, geometry, ks, hitandrun, pdist, fastcluster, compiler, e1071, progress, mvtnorm, data.table, terra, sp, foreach, doParallel, parallel, ggplot2, pbapply, palmerpenguins, purrr, dplyr, caret |
| LinkingTo: | Rcpp, RcppArmadillo, progress |
| Suggests: | rgl, magick, alphahull, knitr, rmarkdown, gridExtra |
| Published: | 2025-06-15 |
| DOI: | 10.32614/CRAN.package.hypervolume |
| Author: | Benjamin Blonder [aut, cre], Cecina Babich Morrow [aut], Stuart Brown [aut], Gregoire Butruille [aut], Daniel Chen [aut], Alex Laini [aut], David J. Harris [aut], Clement Violet [aut] |
| Maintainer: | Benjamin Blonder <benjamin.blonder at berkeley.edu> |
| BugReports: | https://github.com/bblonder/hypervolume/issues |
| License: | GPL-3 |
| URL: | https://github.com/bblonder/hypervolume |
| NeedsCompilation: | yes |
| CRAN checks: | hypervolume results |
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