plot.MCA {FactoMineR}R Documentation

Draw the Multiple Correspondance Analysis (MCA) graphs

Description

Draw the Multiple Correspondance Analysis (MCA) graphs.

Usage

plot.MCA (x, axes = c(1, 2), 
    xlim = NULL, ylim = NULL, invisible = NULL,
    col.ind = "blue", col.var = "red", col.quali.sup = "darkred",
    col.ind.sup = "darkblue", col.quanti.sup = "black",
    label = "all", cex = 1, title = NULL, habillage = "none", 
    palette = NULL, new.plot = TRUE, ...)

Arguments

x an object of class MCA
axes a length 2 vector specifying the components to plot
xlim range for the plotted 'x' values, defaulting to the range of the finite values of 'x'
ylim range for the plotted 'y' values, defaulting to the range of the finite values of 'y'
invisible string indicating if some points should not be drawn ("ind", "var", "ind.sup", "quali.sup", "quanti.sup")
col.ind a color for the individuals, if color ="none" the label is not written
col.var a color for the categories of qualitative variables, if color ="none" the label is not written
col.quali.sup a color for the qualitative supplementary variables, if color ="none" the label is not written
col.ind.sup a color for the supplementary individuals only if there is not habillage, if color ="none" the label is not written
col.quanti.sup a color for the supplementary quantitative variables, if color ="none" the label is not written
label print the labels of the points
cex cf. function par in the graphics package
title string corresponding to the title of the graph you draw (by default NULL and a title is chosen)
habillage string corresponding to the color which are used. If "none", one color is used for the individual, another one for the qualitative variables; if "quali", one color is used for each qualitative variables; else if it is the position of a qualitative variable, it colors according to the different categories of this variable
palette the color palette used to draw the points. By default colors are chosen. If you want to define the colors : palette=palette(c("black","red","blue")); or you can use: palette=palette(rainbow(30)), or in black and white for example: palette=palette(gray(seq(0,.9,len=25)))
new.plot boolean, if TRUE, a new graphical device is created
... further arguments passed to or from other methods

Value

Returns the individuals factor map and the variables factor map.

Author(s)

Jeremy Mazet, Francois Husson Francois.Husson@agrocampus-ouest.fr

See Also

MCA


[Package FactoMineR version 1.10 Index]