Aproximate Hypervolume for Multivariate Data
Computes a simple approximation to the hypervolume of a multivariate data set.
hypvol(data, reciprocal=FALSE)
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. |
Returns the minimum of the hypervolume computed from simple variable bounds
and that computed from variable bounds of the principal component scores.
Used for the default hypervolume parameter for the noise
component when observations are designated as noise in Mclust
and mclustBIC.
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.
hypvol(iris[,-5])
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.