multiMCA: Multiple Factor Analysis In GDAtools: Geometric Data Analysis

 multiMCA R Documentation

Multiple Factor Analysis

Description

Performs Multiple Factor Analysis, drawing on the work of Escofier and Pages (1994). It allows the use of MCA variants (e.g. specific MCA or class specific MCA) as inputs.

Usage

``multiMCA(l_mca, ncp = 5, compute.rv = FALSE)``

Arguments

 `l_mca` a list of objects of class `MCA`, `speMCA` or `csMCA` `ncp` number of dimensions kept in the results (default is 5) `compute.rv` whether RV coefficients should be computed or not (default is FALSE, which makes the function execute faster)

Details

This function binds individual coordinates from every MCA in `l_mca` argument, weights them by the first eigenvalue, and the resulting data frame is used as input for Principal Component Analysis (PCA).

Value

Returns an object of class `multiMCA`, i.e. a list:

 `eig` a list of numeric vector for eigenvalues, percentage of variance and cumulative percentage of variance `var` a list of matrices with results for input MCAs components (coordinates, correlations between variables and axes, squared cosines, contributions) `ind` a list of matrices with results for individuals (coordinates, squared cosines, contributions) `call` a list with informations about input data `VAR` a list of matrices with results for categories and variables in the input MCAs (coordinates, squared cosines, test-values, variances) `my.mca` lists the content of the objects in `l_mca` argument `RV` a matrix of RV coefficients

Nicolas Robette

References

Escofier, B. and Pages, J. (1994) "Multiple Factor Analysis (AFMULT package)". Computational Statistics and Data Analysis, 18, 121-140.

`plot.multiMCA`, `speMCA`, `csMCA`

Examples

``````data(Taste)
# specific MCA on music variables of Taste example data set
mca1 <- speMCA(Taste[,1:5], excl = c(3,6,9,12,15))
# specific MCA on movie variables of Taste example data set
mca2 <- speMCA(Taste[,6:11], excl = c(3,6,9,12,15,18))
# Multiple Factor Analysis of the two sets of variables
mfa <- multiMCA(list(mca1,mca2))
plot.multiMCA(mfa)
``````

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