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
|
\name{dimdesc}
\alias{dimdesc}
\title{Dimension description}
\description{
This function is designed to point out the variables and the categories that are the most characteristic according
to each dimension obtained by a Factor Analysis. \cr
}
\usage{
dimdesc(res, axes = 1:3, proba = 0.05)}
\arguments{
\item{res}{an object of class PCA, MCA, CA, MFA or HMFA}
\item{axes}{a vector with the dimensions to describe}
\item{proba}{the significance threshold considered to characterized the dimension (by default 0.05)}
}
\value{
Returns a list including:
\item{quanti}{the description of the dimensions by the quantitative variables. The variables are sorted.}
\item{quali}{the description of the dimensions by the categorical variables}
}
\references{
Husson, F., Le, S. and Pages, J. (2010). Exploratory Multivariate Analysis by Example Using R, \emph{Chapman and Hall}.
}
\author{Francois Husson \email{francois.husson@institut-agro.fr}}
\seealso{ \code{\link{PCA}}, \code{\link{CA}}, \code{\link{MCA}}, \code{\link{MFA}}, \code{\link{HMFA}},\cr
\href{https://www.youtube.com/watch?v=Uhw-1NilmAk&list=PLnZgp6epRBbTsZEFXi_p6W48HhNyqwxIu&index=9}{Video showing how to use this function}}
\examples{
data(decathlon)
res.pca <- PCA(decathlon, quanti.sup = 11:12, quali.sup=13, graph=FALSE)
dimdesc(res.pca)
}
\keyword{multivariate}
|
