contrib: Contributions of active variables

In GDAtools: Geometric Data Analysis

Contributions of active variables

Description

From MCA results, computes contributions of categories and variables to the axes and the overall cloud.

Usage

contrib(resmca)

Arguments

resmca

object of class MCA, speMCA or csMCA

Details

The contribution of a point to an axis depends both on the distance from the point to the origin point along the axis and on the weight of the point. The contributions of points to axes are the main aid to interpretation (see Le Roux and Rouanet, 2004 and 2010).

Value

A list of data frames:

ctr	Data frame with the contributions of categories to axes
var.ctr	Data frame with the contributions of variables to axes
ctr.cloud	Data frame with the contributions of categories to the overall cloud
vctr.cloud	Data frame with the contributions of variables to the overall cloud

Author(s)

Nicolas Robette

References

Le Roux B. and Rouanet H., Multiple Correspondence Analysis, SAGE, Series: Quantitative Applications in the Social Sciences, Volume 163, CA:Thousand Oaks (2010).

Le Roux B. and Rouanet H., Geometric Data Analysis: From Correspondence Analysis to Stuctured Data Analysis, Kluwer Academic Publishers, Dordrecht (June 2004).

See Also

speMCA, supvar, tabcontrib

Examples

# specific MCA on the Music example data set
data(Music)
junk <- c("FrenchPop.NA", "Rap.NA", "Rock.NA", "Jazz.NA", "Classical.NA")
mca <- speMCA(Music[,1:5], excl = junk)
# contributions of variables
contrib(mca)

GDAtools documentation built on Oct. 6, 2023, 5:07 p.m.