R: Summarizing discriminant analysis based on Gaussian finite...

summary.MclustDA {mclust}

R Documentation

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

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

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

[Package mclust version 5.3 Index]