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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 |
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Author | Benjamin 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] |
Maintainer | Benjamin Blonder <benjamin.blonder@berkeley.edu> |
License | GPL-3 |
Version | 3.1.5 |
URL | https://github.com/bblonder/hypervolume |
Package repository | View on CRAN |
Installation |
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