expectation_box: Hyperbox expectation

In dc165/Hypervolume-Dev: High Dimensional Geometry and Set Operations Using Kernel Density Estimation, Support Vector Machines, and Convex Hulls

Description

Generates expectation hypervolume corresponding to an axis-aligned hyperbox that minimally encloses the data.

Usage

expectation_box(input, point.density = NULL, num.samples = NULL, use.random = FALSE)

Arguments

input	A m x n matrix or data frame, where m is the number of observations and n is the dimensionality.
point.density	The point density of the output expectation. If NULL, defaults to v / num.points where d is the dimensionality of the input and v is the volume of the hypersphere.
num.samples	The number of points in the output expectation. If NULL, defaults to 10^(3+sqrt(ncol(d))) where d is the dimensionality of the input. num.points has priority over point.density; both cannot be specified.
use.random	If TRUE and the input is of class Hypervolume, sets boundaries based on the @RandomPoints slot; otherwise uses @Data.

Value

A Hypervolume-class object corresponding to the expectation.

Examples

data(iris)
e_box <- expectation_box(iris[,1:3])

dc165/Hypervolume-Dev documentation built on Dec. 13, 2020, 6:02 p.m.