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.
- Version3.1.4
- R versionunknown
- LicenseGPL-3
- Needs compilation?Yes
- Last release05/01/2024
Documentation
Team
Benjamin Blonder
David J. Harris
Show author detailsRolesContributorCecina Babich Morrow
Show author detailsRolesContributorStuart Brown
Show author detailsRolesContributorGregoire Butruille
Show author detailsRolesContributorDaniel Chen
Show author detailsRolesContributorAlex Laini
Show author detailsRolesContributor
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Dependencies
- Depends1 package
- Imports22 packages
- Suggests6 packages
- Linking To3 packages
- Reverse Imports4 packages
- Reverse Suggests2 packages