Package: hypervolume
Type: Package
Title: High Dimensional Geometry, Set Operations, Projection, and
        Inference Using Kernel Density Estimation, Support Vector
        Machines, and Convex Hulls
Version: 3.0.2
Date: 2022-01-31
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@berkeley.edu>
Description: 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.
License: GPL-3
Depends: Rcpp, methods, R (>= 3.0.2)
LinkingTo: Rcpp, RcppArmadillo, progress
Imports: raster, maps, MASS, geometry, ks, pdist, fastcluster,
        compiler, e1071, hitandrun, progress, mvtnorm, data.table,
        rgeos, sp, foreach, doParallel, parallel, ggplot2, pbapply,
        palmerpenguins, purrr, dplyr, caret
Suggests: rgl, magick, alphahull, knitr, rmarkdown, gridExtra
NeedsCompilation: yes
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Packaged: 2022-01-31 23:58:47 UTC; benjaminblonder
Repository: CRAN
Date/Publication: 2022-02-01 00:30:02 UTC
Built: R 4.0.5; x86_64-w64-mingw32; 2022-04-18 08:12:19 UTC; windows
Archs: i386, x64
