R: Fuzzy Correspondence Analysis and Fuzzy Principal Components...
dudi.fca
R Documentation
Fuzzy Correspondence Analysis and Fuzzy Principal Components Analysis
Description
Theses functions analyse a table of fuzzy variables.
A fuzzy variable takes values of type a=(a1,…,ak)
giving the importance of k categories.
A missing data is denoted (0,...,0).
Only the profile a/sum(a) is used, and missing data are replaced by
the mean profile of the others in the function prep.fuzzy.var. See ref. for details.
a vector containing the number of categories for each fuzzy variable
row.w
a vector of row weights
scannf
a logical value indicating whether the eigenvalues bar plot should be displayed
nf
if scannf FALSE, an integer indicating the number of kept axes
Value
The function prep.fuzzy.var returns a data frame with the attribute col.blocks.
The function dudi.fca returns a list of class fca and dudi (see dudi) containing also
cr
a data frame which rows are the blocs, columns are the kept axes, and values are the correlation ratios.
The function dudi.fpca returns a list of class pca and dudi (see dudi) containing also