hypervolume: High Dimensional Geometry and Set Operations Using Kernel Density Estimation, Support Vector Machines, and Convex Hulls
Version 2.0.7

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, with contributions from David J. Harris
Date of publication2017-08-07 07:09:35 UTC
MaintainerBenjamin Blonder <bblonder@gmail.com>
Package repositoryView on CRAN
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hypervolume documentation built on Aug. 7, 2017, 9:02 a.m.