summary.MclustDA: Summarizing discriminant analysis based on Gaussian finite mixture modeling.

Description

Summary method for class "MclustDA".

Usage

# S3 method for MclustDA
summary(object, parameters = FALSE, newdata, newclass, …)
# S3 method for summary.MclustDA
print(x, digits = getOption("digits"), …)

Arguments

object

An object of class 'MclustDA' resulting from a call to MclustDA.

An object of class 'summary.MclustDA', usually, a result of a call to summary.MclustDA.

parameters

Logical; if TRUE, the parameters of mixture components are printed.

newdata

A data frame or matrix giving the test data.

newclass

A vector giving the class labels for the observations in the test data.

digits

The number of significant digits to use when printing.

…

Further arguments passed to or from other methods.

Value

The function summary.MclustDA computes and returns a list of summary statistics of the estimated MclustDA or EDDA model for classification.

References

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

C. Fraley, A. E. Raftery, T. B. Murphy and L. Scrucca (2012). mclust Version 4 for R: Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation. Technical Report No. 597, Department of Statistics, University of Washington.

Examples

Run this code

# NOT RUN {
mod = MclustDA(data = iris[,1:4], class = iris$Species)
summary(mod)
summary(mod, parameters = TRUE)
# }