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: | 3.1.4 |
---|---|
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: | 2024-05-01 |
DOI: | 10.32614/CRAN.package.hypervolume |
Author: | Benjamin Blonder, with contributions from Cecina Babich Morrow, Stuart Brown, Gregoire Butruille, Daniel Chen, Alex Laini, and David J. Harris |
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 |
Documentation:
Downloads:
Reverse dependencies:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=hypervolumeto link to this page.