ade4 (version 1.7-5)

pcaivortho: Principal Component Analysis with respect to orthogonal instrumental variables

Description

performs a Principal Component Analysis with respect to orthogonal instrumental variables.

Usage

pcaivortho(dudi, df, scannf = TRUE, nf = 2)
"summary"(object, ...)

Arguments

dudi

a duality diagram, object of class dudi

df

a data frame with the same rows

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

object

an object of class pcaiv

...

further arguments passed to or from other methods

Value

an object of class 'pcaivortho' sub-class of class dudi

References

Rao, C. R. (1964) The use and interpretation of principal component analysis in applied research. Sankhya, A 26, 329--359. Sabatier, R., Lebreton J. D. and Chessel D. (1989) Principal component analysis with instrumental variables as a tool for modelling composition data. In R. Coppi and S. Bolasco, editors. Multiway data analysis, Elsevier Science Publishers B.V., North-Holland, 341--352

Examples

## Not run: 
# data(avimedi)
# cla <- avimedi$plan$reg:avimedi$plan$str
# # simple ordination
# coa1 <- dudi.coa(avimedi$fau, scan = FALSE, nf = 3)
# # within region
# w1 <- wca(coa1, avimedi$plan$reg, scan = FALSE)
# # no region the same result
# pcaivnonA <- pcaivortho(coa1, avimedi$plan$reg, scan = FALSE)
# summary(pcaivnonA)
# # region + strate
# interAplusB <- pcaiv(coa1, avimedi$plan, scan = FALSE)
# 
# if(adegraphicsLoaded()) {
#   g1 <- s.class(coa1$li, cla, psub.text = "Sans contrainte", plot = F)
#   g21 <- s.match(w1$li, w1$ls, plab.cex = 0, psub.text = "Intra Région", plot = F)
#   g22 <- s.class(w1$li, cla, plot = F)
#   g2 <- superpose(g21, g22)
#   g31 <- s.match(pcaivnonA$li, pcaivnonA$ls, plab.cex = 0, psub.tex = "Contrainte Non A", plot = F)
#   g32 <- s.class(pcaivnonA$li, cla, plot = FALSE)
#   g3 <- superpose(g31, g32)
#   g41 <- s.match(interAplusB$li, interAplusB$ls, plab.cex = 0, psub.text = "Contrainte A + B", 
#     plot = F)
#   g42 <- s.class(interAplusB$li, cla, plot = F)
#   g4 <- superpose(g41, g42)
#   G <- ADEgS(list(g1, g2, g3, g4), layout = c(2, 2))
# 
# } else {
#   par(mfrow = c(2, 2))
#   s.class(coa1$li, cla, sub = "Sans contrainte")
#   s.match(w1$li, w1$ls, clab = 0, sub = "Intra Région")
#   s.class(w1$li, cla, add.plot = TRUE)
#   s.match(pcaivnonA$li, pcaivnonA$ls, clab = 0, sub = "Contrainte Non A")
#   s.class(pcaivnonA$li, cla, add.plot = TRUE)
#   s.match(interAplusB$li, interAplusB$ls, clab = 0, sub = "Contrainte A + B")
#   s.class(interAplusB$li, cla, add.plot = TRUE)
#   par(mfrow = c(1,1))
# }## End(Not run)