dudi.fca {ade4} | 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=(a_1,\dots,a_k)
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.
Usage
prep.fuzzy.var (df, col.blocks, row.w = rep(1, nrow(df)))
dudi.fca(df, scannf = TRUE, nf = 2)
dudi.fpca(df, scannf = TRUE, nf = 2)
Arguments
df |
a data frame containing positive or null values |
col.blocks |
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
cent
norm
blo
indica
FST
inertia
Author(s)
Daniel Chessel
Anne-Béatrice Dufour anne-beatrice.dufour@univ-lyon1.fr
References
Chevenet, F., Dolédec, S. and Chessel, D. (1994) A fuzzy coding approach for the analysis of long-term ecological data. Freshwater Biology, 31, 295–309.
Examples
w1 <- matrix(c(1,0,0,2,1,1,0,2,2,0,1,0,1,1,1,0,1,3,1,0), 4, 5)
w1 <- data.frame(w1)
w2 <- prep.fuzzy.var(w1, c(2, 3))
w1
w2
attributes(w2)
data(bsetal97)
w <- prep.fuzzy.var(bsetal97$biol, bsetal97$biol.blo)
if(adegraphicsLoaded()) {
g1 <- plot(dudi.fca(w, scann = FALSE, nf = 3), plabels.cex = 1.5)
} else {
scatter(dudi.fca(w, scann = FALSE, nf = 3), csub = 3, clab.moda = 1.5)
scatter(dudi.fpca(w, scann = FALSE, nf = 3), csub = 3, clab.moda = 1.5)
}
## Not run:
w1 <- prep.fuzzy.var(bsetal97$biol, bsetal97$biol.blo)
w2 <- prep.fuzzy.var(bsetal97$ecol, bsetal97$ecol.blo)
d1 <- dudi.fca(w1, scannf = FALSE, nf = 3)
d2 <- dudi.fca(w2, scannf = FALSE, nf = 3)
plot(coinertia(d1, d2, scannf = FALSE))
## End(Not run)