plot.MCA: Draw the Multiple Correspondence Analysis (MCA) graphs

In FactoMineR: Multivariate Exploratory Data Analysis and Data Mining

Draw the Multiple Correspondence Analysis (MCA) graphs

Description

Draw the Multiple Correspondence Analysis (MCA) graphs.

Usage

## S3 method for class 'MCA'
plot(x, axes = c(1, 2), choix=c("ind","var","quanti.sup"),
    xlim = NULL, ylim = NULL, 
    invisible = c("none","ind","var","ind.sup","quali.sup","quanti.sup"),
    col.ind = "black", col.var = "red", col.quali.sup = "darkgreen",
    col.ind.sup = "blue", col.quanti.sup = "blue",
    label = c("all","none","ind","var","ind.sup","quali.sup","quanti.sup"),
    title = NULL, habillage = "none", 
    palette = NULL, autoLab = c("auto","yes","no"), new.plot = FALSE, 
    select = NULL, selectMod = NULL, unselect = 0.7, 
	shadowtext = FALSE, legend = list(bty = "y", x = "topleft"), 
	graph.type = c("ggplot","classic"), ggoptions = NULL, ...)

Arguments

x	an object of class MCA
axes	a length 2 vector specifying the components to plot
choix	the graph to plot ("ind" for the individuals and the categories, "var" for the variables, "quanti.sup" for the supplementary quantitative variables)
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 categorical variables, if color ="none" the label is not written
col.quali.sup	a color for the categorical 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; "all" print all the labels; may be a vector with "ind" (for the individuals),"ind.sup" (for the supplementary individuals),"var" (for the active categories), "quali.sup" "var" (for the supplementary categories)
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 categorical variables; if "quali", one color is used for each categorical variables; else if it is the position of a categorical 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)))
autoLab	if autoLab="auto", autoLab is equal to "yes" if there are less than 50 elements and "no" otherwise; if "yes", the labels of the drawn elements are placed in a "good" way (can be time-consuming if many elements), and if "no" the elements are placed quickly but may overlap
new.plot	boolean, if TRUE, a new graphical device is created
select	a selection of the elements that are drawn; see the details section
selectMod	a selection of the categories that are drawn; see the details section
unselect	may be either a value between 0 and 1 that gives the transparency of the unselected objects (if unselect=1 the transparceny is total and the elements are not drawn, if unselect=0 the elements are drawn as usual but without any label) or may be a color (for example unselect="grey60")
shadowtext	boolean; if true put a shadow on the labels (rectangles are written under the labels which may lead to difficulties to modify the graph with another program)
legend	a list of arguments that defines the legend if needed (when individuals are drawn according to a variable); see the arguments of the function legend
graph.type	a character that gives the type of graph used: "ggplot" or "classic"
ggoptions	a list that gives the graph options when grah.type="ggplot" is used. See the optines and the default values in the details section
...	further arguments passed to or from other methods, such as cex, cex.main, ...

Details

The argument autoLab = "yes" is time-consuming if there are many labels that overlap. In this case, you can modify the size of the characters in order to have less overlapping, using for example cex=0.7.
The select argument can be used in order to select a part of the elements (individuals if you draw the graph of individuals, or variables if you draw the graph of variabless) that are drawn. For example, you can use:
select = 1:5 and then the elements 1:5 are drawn.
select = c("name1","name5") and then the elements that have the names name1 and name5 are drawn.
select = "coord 10" and then the 10 elements that have the highest (squared) coordinates on the 2 chosen dimensions are drawn.
select = "contrib 10" and then the 10 elements that have the highest contribution on the 2 dimensions of your plot are drawn.
select = "cos2 5" and then the 5 elements that have the highest cos2 on the 2 dimensions of your plot are drawn.
select = "dist 8" and then the 8 elements that have the highest distance to the center of gravity are drawn.
The selectMod argument can be used in order to select the categories that are drawn.

Value

Returns the individuals factor map and the variables factor map.

Author(s)

Francois Husson [e-mail]

See Also

MCA

Examples

data (poison)
res.mca = MCA (poison, quali.sup = 3:4, quanti.sup = 1:2, graph=FALSE)
plot(res.mca,invisible=c("var","quali.sup"))
plot(res.mca,invisible="ind")
plot(res.mca,choix="var")
plot(res.mca,invisible=c("ind"), selectMod="cos2 10")
## Not run: 
plot(res.mca, selectMod="cos2 5", select="cos2 5")

## You can modify the ggplot graphs as ususal with ggplot2
require(ggplot2)
gr <- plot(res.mca)
gr + theme(panel.grid.major = element_blank(),
   plot.title=element_text(size=14, color="blue"),
   axis.title = element_text(size=12, color="red"))

## End(Not run)

FactoMineR documentation built on May 29, 2024, 3:36 a.m.