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

In mclust: Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

Summarizing discriminant analysis based on Gaussian finite mixture modeling

Description

Summary method for class "MclustDA".

Usage

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

Arguments

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

Author(s)

Luca Scrucca

See Also

MclustDA, plot.MclustDA.

Examples

mod = MclustDA(data = iris[,1:4], class = iris$Species)
summary(mod)
summary(mod, parameters = TRUE)

mclust documentation built on Nov. 16, 2023, 5:10 p.m.