hypervolume: High Dimensional Geometry, Set Operations, Projection, and Inference 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.

Package details

AuthorBenjamin 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]
MaintainerBenjamin Blonder <benjamin.blonder@berkeley.edu>
LicenseGPL-3
Version3.1.5
URL https://github.com/bblonder/hypervolume
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("hypervolume")

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hypervolume documentation built on April 4, 2025, 12:46 a.m.