description {FactoInvestigate}

Factorial dimensions description

Description

Describe a couple of dimensions, giving the individuals specific to each dimension, and the variables that characterize each group of individuals.

Usage

description(res, file = "", dim = 1:2, desc = dim, Iselec = "contrib", 
            Vselec = "cos2", Rselec = "cos2", Cselec = "cos2", Icoef = 1, 
            Vcoef = 1, Rcoef = 1, Ccoef = 1, mmax = 10, nmax = 10)

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).

desc

a 2 dimensional numerical vector giving the factorial dimensions to describe (by default the dim value).

Iselec

the individuals to select; see the details section.

Vselec

the variables to select; see the details section.

Rselec

the rows to select (for a CA res object); see the details section.

Cselec

the columns to select (for a CA res object); see the details section.

Icoef

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

Vcoef

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

Rcoef

a numerical coefficient to adjust the rows selection rule (for a CA res object); see the details section.

Ccoef

a numerical coefficient to adjust the columns selection rule (for a CA res object); see the details section.

mmax

an integer giving the maximum number of individuals to illustrate each cluster (by default 10).

nmax

an integer giving the maximum number of variables to illustrate each cluster (by default 10).

Details

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

The Icoef argument (respectively Vcoef, Rcoef or Ccoef) is used in order to adjust the selection of the elements when based on Iselec = "contrib" or Iselec = "cos2". For example :
- if Icoef = 2, the threshold is 2 times higher, and thus 2 times more restrictive.
- if Icoef = 0.5, the threshold is 2 times lower, and thus 2 times less restrictive.

Author(s)

Simon Thuleau and Francois Husson

See Also

classif

Examples

## Not run: 
require(FactoMineR)
data(decathlon)
res.pca = PCA(decathlon, quanti.sup = c(11:12), quali.sup = c(13), graph = FALSE)
description(res.pca, file = "PCA.Rmd", dim = 1:2)

## End(Not run)