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: |
3.0.4 |
| Depends: |
Rcpp, methods, R (≥ 3.0.2) |
| Imports: |
raster, maps, MASS, geometry, ks, hitandrun, pdist, fastcluster, compiler, e1071, progress, mvtnorm, data.table, rgeos, sp, foreach, doParallel, parallel, ggplot2, pbapply, palmerpenguins, purrr, dplyr, caret |
| LinkingTo: |
Rcpp, RcppArmadillo, progress |
| Suggests: |
rgl, magick, alphahull, knitr, rmarkdown, gridExtra |
| Published: |
2022-05-28 |
| Author: |
Benjamin Blonder, with contributions from Cecina Babich Morrow, David J. Harris, Stuart Brown, Gregoire Butruille, Alex Laini, and Dan Chen |
| Maintainer: |
Benjamin Blonder <benjamin.blonder at berkeley.edu> |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| CRAN checks: |
hypervolume results |