ade4 (version 1.7-5)

pcaiv: Principal component analysis with respect to instrumental variables

Description

performs a principal component analysis with respect to instrumental variables.

Usage

pcaiv(dudi, df, scannf = TRUE, nf = 2)
"plot"(x, xax = 1, yax = 2, ...) 
"print"(x, ...)
"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

x, object

an object of class pcaiv

xax

the column number for the x-axis

yax

the column number for the y-axis

...

further arguments passed to or from other methods

Value

returns an object of class pcaiv, 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. Obadia, J. (1978) L'analyse en composantes explicatives. Revue de Statistique Appliquee, 24, 5--28. Lebreton, J. D., Sabatier, R., Banco G. and Bacou A. M. (1991) Principal component and correspondence analyses with respect to instrumental variables : an overview of their role in studies of structure-activity and species- environment relationships. In J. Devillers and W. Karcher, editors. Applied Multivariate Analysis in SAR and Environmental Studies, Kluwer Academic Publishers, 85--114.

Examples

data(rhone)
pca1 <- dudi.pca(rhone$tab, scan = FALSE, nf = 3)
iv1 <- pcaiv(pca1, rhone$disch, scan = FALSE)
summary(iv1)
plot(iv1)