Learn R Programming

ade4 (version 1.01)

score.pca: Graphs to Analyse a factor in PCA

Description

represents the graphs of a factor in a principal component analysis.

Usage

score.pca(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

Examples

Run this code
data(deug)
dd1 <- dudi.pca(deug$tab, scan = FALSE)
score(dd1, csub = 3)
 
# 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

Run the code above in your browser using DataLab