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.