hypervolume (version 2.0.12)
High Dimensional Geometry and Set Operations Using Kernel
Density Estimation, Support Vector Machines, and Convex Hulls
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.