R: Graphs to Analyse a factor in PCA

score.pca {ade4}

R Documentation

Graphs to Analyse a factor in PCA

Description

performs the canonical graph of a Principal Component Analysis.

Usage

## S3 method for class '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(s)

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

[Package ade4 version 1.7-4 Index]