# plot.acp: Graphics for Principal component Analysis In amap: Another Multidimensional Analysis Package

## Description

Graphics for Principal component Analysis

## Usage

 ```1 2 3 4 5 6 7 8 9``` ```## 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

 ```1 2 3 4``` ```data(lubisch) lubisch <- lubisch[,-c(1,8)] p <- acp(lubisch) plotAll(p) ```