ade4 (version 1.7-19)

score.pca: Graphs to Analyse a factor in PCA

Description

performs the canonical graph of a Principal Component Analysis.

Usage

# S3 method for pca
score(x, xax = 1, which.var = NULL, mfrow = NULL, csub = 2, 
    sub = names(x$tab), abline = TRUE, ...)

Arguments

x

an object of class pca

xax

the column number for the used axis

which.var

the numbers of the kept columns for the analysis, otherwise all columns

mfrow

a vector of the form "c(nr,nc)", otherwise computed by a special own function n2mfrow

csub

a character size for sub-titles, used with par("cex")*csub

sub

a vector of string of characters to be inserted as sub-titles, otherwise the names of the variables

abline

a logical value indicating whether a regression line should be added

...

further arguments passed to or from other methods

Author

Daniel Chessel

Examples

data(deug)
dd1 <- dudi.pca(deug$tab, scan = FALSE)
score(dd1)
 
# The correlations are :
dd1$co[,1]
# [1] 0.7925 0.6532 0.7410 0.5287 0.5539 0.7416 0.3336 0.2755 0.4172