High Dimensional Geometry, Set Operations, Projection, and Inference Using Kernel Density Estimation, Support Vector Machines, and Convex Hulls
Generate hypervolumes using pre-existing parameters
Kernel bandwidth estimators for hypervolumes
Hypersphere expectation
Hyperbox expectation
Convex expectation
Maximal expectation
Find optimal parameters to calculate occupancy
Get weighted centroid of hypervolume or hypervolume list
Get centroid of hypervolume or hypervolume list
Volume of the intersection of a bootstrapped occupancy object
Stats from occupancy objects
Volume of the unshared fraction of a bootstrapped occupancy object
Extract the volume from occupancy bootstrap objects
Extract the relative volume
Extract volume
Hypervolume construction via hyperbox kernel density estimation
Distance from a point to the margin of a hypervolume.
Distance between two hypervolumes
Estimate probability a given location
Hypervolumes at different sample sizes
Hypervolume construction via Gaussian kernel density estimation
Generates hypervolume by sampling from arbitrary model object.
Hole detection
Inclusion test
Concatenate hypervolumes
Hypervolumes through permuting labels of n pairwise groups of hypervol...
Significance of random points occupancy
Operations for groups of hypervolumes
Bootstrap n hypervolumes
Confidence intervals for overlap statistics
Overlap statistics for set operations (Sorensen, Jaccard, etc.)
Null distribution for overlap statistics
Hypervolumes through permuting data of two hypervolumes
Geographical projection of hypervolume for species distribution modeli...
Removes small hypervolumes from a HypervolumeList
Redundancy of a point in a hypervolume
Hypervolume resampling methods
Saves animated GIF of three-dimensional hypervolume plot.
Segments a hypervolume into multiple separate hypervolumes.
Multi-way set intersection
Multi-way set union
Set operations (intersection / union / unique components)
Hypervolume construction via one-class support vector machine (SVM) le...
Reduces the number of random points in a hypervolume
Thresholds hypervolume and calculates volume quantile statistics (empi...
Convert hypervolumes to data.frame
Hypervolume variable importance
Class "Hypervolume"
tools:::Rd_package_title("hypervolume")
Hypervolume construction methods
Class "HypervolumeList"
Morphological data for Darwin's finches
Goodness of fit metrics for bootstrapped occupancy objects
Subset occupancy hypervolumes
Get the intersection of an occupancy object
Union of hypervolumes from an occupancy object
Unshared fraction from an occupancy object
Generates axis-wise range limits with padding
Plot a hypervolume or list of hypervolumes
Print summary of hypervolume
Data and demo for Quercus (oak) tree distributions
Summary of hypervolume
Read hypervolumes from directory
Abundance weighting and prior of data for hypervolume input
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.