graphSup {FactoInvestigate} | R Documentation |
Supplementary variables factor map
Description
Realise the optimised graph of supplementary variables
Usage
graphSup(res, file = "", dim = 1:2, Mselec = "cos2", Mcoef = 1,
figure.title = "Figure", graph = TRUE, cex = 0.7, options=NULL)
Arguments
res |
an object of class PCA, CA or MCA. |
file |
the file path where to write the description in Rmarkdown language. If not specified, the description is written in the console. |
dim |
a 2 dimensional numerical vector giving the factorial dimensions to use for the representation (by default the first plane). |
Mselec |
the supplementary variables to select ; see the details section. |
Mcoef |
a numerical coefficient to adjust the supplementary variables selection rule ; see the details section. |
figure.title |
the text label to add before graph title. |
graph |
a boolean : if |
cex |
an optional argument for the generic plot functions, used to adjust the size of the elements plotted. |
options |
a character string that gives the output options fir the figures.
If NULL, |
Details
The Mselec
argument is used in order to select a part of the illustrative variables that are drawn and described. For example, you can use either :
- Mselec = 1:5
then the illustrative variables numbered 1 to 5 are drawn.
- Mselec = c("name1","name5")
then the illustrative variables named name1
and name5
are drawn.
- Mselec = "cos2 5"
then the 5 illustrative variables that have the highest cos2 on the 2 dimensions of the plane are drawn.
- Mselec = "cos2 0.8"
then the illustrative variables that have a cos2
higher to 0.8
on the plane are drawn.
- Mselec = "cos2"
then the optimal number of illustrative variables that have the highest cos2 on the 2 dimensions of the plane are drawn.
The Mcoef
argument is used in order to adjust the selection of the illustrative variables when based on Mselec = "cos2"
. For example :
- if Mcoef = 2
, the threshold is 2 times higher, and thus 2 times more restrictive.
- if Mcoef = 0.5
, the threshold is 2 times lower, and thus 2 times less restrictive.
Author(s)
Simon Thuleau and Francois Husson
See Also
factoGraph
, graphInd
, graphHab
, graphCA
, graphVar
Examples
## Not run:
require(FactoMineR)
data(decathlon)
res.pca = PCA(decathlon, quanti.sup = c(11:12), quali.sup = c(13), graph = FALSE)
graphSup(res.pca)
## End(Not run)