bblonder/hypervolume: High Dimensional Geometry and Set Operations Using Kernel Density Estimation, Support Vector Machines, and Convex Hulls

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.

Getting started

Package details

AuthorBenjamin Blonder, with contributions from David J. Harris
MaintainerBenjamin Blonder <bblonder@gmail.com>
LicenseGPL-3
Version2.0.12
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("bblonder/hypervolume")
bblonder/hypervolume documentation built on Dec. 10, 2019, 1:25 a.m.