Approximate hypervolume for multivariate data — hypvolunif • mclustAddons

Simple approximations for the hypervolume of a multivariate dataset by assuming a uniform distribution.

Usage

hypvolunif(data, pc = FALSE, logarithm = TRUE, ...)

data: A numeric vector, matrix, or data frame. If a matrix or data frame, rows correspond to observations and columns correspond to variables. Categorical variables and missing values are not allowed.
pc: A logical value indicating whether the volume of hyperectangle enclosing the data (FALSE) or the volume of hyperectangle aligned with the principal axes enclosing the data should be computed.
logarithm: A logical value indicating whether or not the logarithm of the hypervolume should be returned.
...: Further arguments passed to or from other methods.

Returns the (log) hypervolume from a uniform distribution aligned with the original axes or along the principal components.

Luca Scrucca

x1 = rnorm(1000)
x2 = 0.8*x1 + rnorm(1000)
x = cbind(x1, x2)
hypvolunif(x)
#> [1] 3.770216
hypvolunif(x, pc = TRUE)
#> [1] 3.610257