selection: Graphical elements selection

Description

Select the best elements to plot in a graph

Usage

selection(res, dim = 1:2, margin = 1, selec = "cos2", coef = 1)

Arguments

res

an object of class PCA, CA or MCA.

dim

a 2 dimensional numerical vector giving the factorial dimensions to use for the representation (by default the first plane).

margin

an integer (by default 1). If equals 1, the function computes on the individuals (or rows). If equals 2, the function computes on the active variables (or columns). If equals 3, the function computes on the supplementary variables.

selec

the elements to select ; see the details section.

coef

a numerical coefficient to adjust the elements selection rule ; see the details section.

Value

drawn

the elements selected.

what.drawn

the criterion of selection (as a sentence).

Details

The selec argument is used in order to select a part of the elements that are drawn and described. For example, you can use either : - selec = 1:5 then the elements numbered 1 to 5 are drawn. - selec = c("name1","name5") then the elements named name1 and name5 are drawn. - selec = "contrib 10" then the 10 active or illustrative elements that have the highest contribution on the 2 dimensions of the plane are drawn. - selec = "contrib" then the optimal number of active or illustrative elements that have the highest contribution on the 2 dimensions of the plane are drawn. - selec = "cos2 5" then the 5 active or illustrative elements that have the highest cos2 on the 2 dimensions of the plane are drawn. - selec = "cos2 0.8" then the active or illustrative elements that have a cos2 higher to 0.8 on the plane are drawn. - selec = "cos2" then the optimal number of active or illustrative elements that have the highest cos2 on the 2 dimensions of the plane are drawn.

The coef argument is used in order to adjust the selection of the elements when based on selec = "contrib" or selec = "cos2". For example : - if coef = 2, the threshold is 2 times higher, and thus 2 times more restrictive. - if coef = 0.5, the threshold is 2 times lower, and thus 2 times less restrictive.

Examples

Run this code

# NOT RUN {
require(FactoMineR)
data(decathlon)
res.pca = PCA(decathlon, quanti.sup = c(11:12), quali.sup = c(13), graph = FALSE)
selection(res.pca, margin = 1, selec = "contrib 10")
# }