plot.acp {amap}R Documentation

Graphics for Principal component Analysis

Description

Graphics for Principal component Analysis / Graphiques pour l'analyse en composantes principales, "comme Carlier"

Usage

plot.acp(x,i=1,j=2,text=TRUE,label='Composante ',col='darkblue',
main='ACP des individus',...)
biplot.acp(x,i=1,j=2,label='Composante ',col='darkblue',length=0.1,
main='ACP des variables',...)
plot2.acp(x,pourcent=FALSE,eigen=TRUE,label='Comp.',col='lightgrey',
main='Eboulis des valeurs propres',ylab='Valeurs propres')

Arguments

x Result of acp / princomp
i X axis
j Y axis
text a logical value indicating whether we use text or points for plot
pourcent a logical value indicating whether we use pourcentage of values
eigen a logical value indicating whether we use eigen values or standard deviation
label label for X and Y axis
col Color of plot
main Title of graphic
ylab Y label
length length of arrows
... cex, pch, and other options; see points.

Value

Graphics:
plot.acp PCA for lines / ACP des individus
plot.acp PCA for columns / ACP des variables
plot2.acp Eigen values diagram / Eboulis des valeurs propres

Author(s)

Antoine Lucas, http://genopole.toulouse.inra.fr/~lucas/amap

See Also

acp,acpgen, princomp

Examples

data(lubisch)
lubisch <- lubisch[,-c(1,8)]
p <- acp(lubisch)
plot(p)

[Package Contents]