mclust (version 3.4.7)

hypvol: Aproximate Hypervolume for Multivariate Data

Description

Computes a simple approximation to the hypervolume of a multivariate data set.

Usage

hypvol(data, reciprocal=FALSE)

Arguments

data

A numeric vector, matrix, or data frame of observations. Categorical variables are not allowed. If a matrix or data frame, rows correspond to observations and columns correspond to variables.

reciprocal

A logical variable indicating whether or not the reciprocal hypervolume is desired rather than the hypervolume itself. The default is to return the hypervolume.

Value

• Computes the hypervolume by two methods: simple variable bounds and principal components, and returns the minimum value. Used to compute the default hypervolume parameter for the noise component in

References

A. Dasgupta and A. E. Raftery (1998). Detecting features in spatial point processes with clutter via model-based clustering. Journal of the American Statistical Association 93:294-302.

C. Fraley and A.E. Raftery (1998). Computer Journal 41:578-588.

C. Fraley and A. E. Raftery (2002). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631.

See Also

mclustBIC

Examples

hypvol(iris[,-5])