Model-based clustering for bounded data

Clustering of bounded data via transformation-based approach for Gaussian mixtures.

Usage

MclustBounded(data, ...)

# S3 method for class 'MclustBounded'
summary(object, classification = TRUE, parameters = FALSE, ...)

Arguments

data: A numeric vector, matrix, or data frame of observations. If a matrix or data frame, rows correspond to observations and columns correspond to variables.
...: Further arguments passed to densityMclustBounded(). For a full description of available arguments see the corresponding help page.
object: An object of class 'MclustBounded'.
classification: A logical, if TRUE a table of MAP classification/clustering of observations is printed.
parameters: A logical, if TRUE the estimated parameters of mixture components are printed.

Value

Returns an object of class 'MclustBounded'.

Details

For more details see vignette("mclustAddons")

References

Scrucca L. (2024) A model-based clustering approach for bounded data using transformation-based Gaussian mixture models. Under review. arXiv pre-print available at http://arxiv.org/abs/2412.13572

Author

Luca Scrucca