plot.acp: Graphics for Principal component Analysis

In amap: Another Multidimensional Analysis Package

Graphics for Principal component Analysis

Description

Graphics for Principal component Analysis

Usage

## S3 method for class 'acp'
plot(x,i=1,j=2,text=TRUE,label='Composants',col='darkblue',
main='Individuals PCA',variables=TRUE,individual.label=NULL,...)
## S3 method for class 'acp'
biplot(x,i=1,j=2,label='Composants',col='darkblue',length=0.1,
main='Variables PCA',circle=TRUE,...)
plot2(x,pourcent=FALSE,eigen=TRUE,label='Comp.',col='lightgrey',
main='Scree Graph',ylab='Eigen Values')
plotAll(x)

Arguments

x	Result of acp or 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
individual.label	labels naming individuals
col	Color of plot
main	Title of graphic
ylab	Y label
length	length of arrows
variables,circle	a logical value indicating whether we display circle or variables
...	cex, pch, and other options; see points.

Value

Graphics:

plot.acp PCA for lines (individuals)

plot.acp PCA for columns (variables)

plot2 Eigen values diagram (Scree Graph)

plotAll Plot both 3 graphs

Author(s)

Antoine Lucas

See Also

acpgen,acprob, princomp

Examples

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

amap documentation built on Oct. 29, 2022, 1:06 a.m.