Last chance! 50% off unlimited learning
Sale ends in
This function performs a projection of supplementary rows (i.e. supplementary individuals).
# S3 method for coa
suprow(x, Xsup, …)
# S3 method for dudi
suprow(x, Xsup, …)
# S3 method for dudi
predict(object, newdata, …)
# S3 method for pca
suprow(x, Xsup, …)
# S3 method for acm
suprow(x, Xsup, …)
# S3 method for mix
suprow(x, Xsup, …)
# S3 method for fca
suprow(x, Xsup, …)
an object of class dudi
an array with the supplementary rows
further arguments passed to or from other methods
predict
returns a data frame containing the coordinates of the supplementary rows. suprow
returns a list with the transformed table Xsup
in tabsup
and the coordinates of the supplementary rows in lisup
.
If suprow.dudi
is used, the column vectors of Xsup are projected without prior modifications onto the principal components of dudi with the scalar product associated to the row weightings of dudi.
Gower, J. C. (1967) Multivariate analysis and multivariate geometry. The statistician, 17, 13--28.
# NOT RUN {
data(euro123)
par(mfrow = c(2, 2))
w <- euro123[[2]]
dudi1 <- dudi.pca(w, scal = FALSE, scan = FALSE)
if(adegraphicsLoaded()) {
g11 <- s.arrow(dudi1$c1, psub.text = "Classical", psub.posi = "bottomright", plot = FALSE)
g12 <- s.label(suprow(dudi1, w)$tabsup, plab.cex = 0.75, plot = FALSE)
g1 <- superpose(g11, g12)
g21 <- s.arrow(dudi1$c1, psub.text = "Without centring", psub.posi = "bottomright", plot = FALSE)
g22 <- s.label(suprow(dudi1, w)$tabsup, plab.cex = 0.75, plot = FALSE)
g2 <- superpose(g21, g22)
g3 <- triangle.label(w, plab.cex = 0.75, label = row.names(w), adjust = FALSE, plot = FALSE)
g4 <- triangle.label(w, plab.cex = 0.75, label = row.names(w), adjust = TRUE, plot = FALSE)
G <- ADEgS(list(g1, g2, g3, g4), layout = c(2, 2))
} else {
s.arrow(dudi1$c1, sub = "Classical", possub = "bottomright", csub = 2.5)
s.label(suprow(dudi1, w), add.plot = TRUE, clab = 0.75)
s.arrow(dudi1$c1, sub = "Without centring", possub = "bottomright", csub = 2.5)
s.label(suprow(dudi1, w), clab = 0.75, add.plot = TRUE)
triangle.plot(w, clab = 0.75, label = row.names(w), scal = FALSE)
triangle.plot(w, clab = 0.75, label = row.names(w), scal = TRUE)
}
data(rpjdl)
rpjdl.coa <- dudi.coa(rpjdl$fau, scann = FALSE, nf = 4)
rpjdl.coa$li[1:3, ]
suprow(rpjdl.coa,rpjdl$fau[1:3, ])$lisup #the same
data(deug)
deug.dudi <- dudi.pca(df = deug$tab, center = deug$cent, scale = FALSE, scannf = FALSE)
suprow(deug.dudi, deug$tab[1:3, ])$lisup #the supplementary individuals are centered
deug.dudi$li[1:3, ] # the same
# }
Run the code above in your browser using DataLab