1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
|
\name{summary.MclustDA}
\alias{summary.MclustDA}
\alias{print.summary.MclustDA}
\title{Summarizing discriminant analysis based on Gaussian finite mixture modeling}
\description{Summary method for class \code{"MclustDA"}.}
\usage{
\method{summary}{MclustDA}(object, parameters = FALSE, newdata, newclass, \dots)
\method{print}{summary.MclustDA}(x, digits = getOption("digits"), \dots)
}
\arguments{
\item{object}{An object of class \code{'MclustDA'} resulting from a call to \code{\link{MclustDA}}.}
\item{x}{An object of class \code{'summary.MclustDA'}, usually, a result of a call to \code{summary.MclustDA}.}
\item{parameters}{Logical; if \code{TRUE}, the parameters of mixture components are printed.}
\item{newdata}{A data frame or matrix giving the test data.}
\item{newclass}{A vector giving the class labels for the observations in
the test data.}
\item{digits}{The number of significant digits to use when printing.}
\item{\dots}{Further arguments passed to or from other methods.}
}
% \details{}
\value{The function \code{summary.MclustDA} computes and returns a list of summary statistics of the estimated MclustDA or EDDA model for classification.}
\author{Luca Scrucca}
% \note{}
\seealso{\code{\link{MclustDA}}, \code{\link{plot.MclustDA}}.}
\examples{
mod = MclustDA(data = iris[,1:4], class = iris$Species)
summary(mod)
summary(mod, parameters = TRUE)
}
\keyword{multivariate}
|
