Graphs to Analyse a factor in PCA

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$tab, scan = FALSE)
score(dd1)
#> Error in s.label(dfxy = cbind(dd1$l1[, 1], deug$tab[1:104, 1L]), plot = FALSE,     storeData = TRUE, pos = -3, paxes = list(aspectratio = "fill",         draw = TRUE), porigin = list(include = FALSE), pgrid = list(        draw = FALSE), plabels = list(cex = 0), psub.text = "Algebra (r=-0.79)"): non convenient selection for dfxy (can not be converted to dataframe)
 
# The correlations are :
dd1$co[,1]
#> [1] -0.7924753 -0.6531896 -0.7410261 -0.5287294 -0.5538660 -0.7416171 -0.3336153
#> [8] -0.2755026 -0.4171874
# [1] 0.7925 0.6532 0.7410 0.5287 0.5539 0.7416 0.3336 0.2755 0.4172