PCA.plot: Principal Component Analysis plotting functions

In ChemometricsWithR: Chemometrics with R - Multivariate Data Analysis in the Natural Sciences and Life Sciences

Description

Plotting functions for PCA: for scores, loadings, scores and loadings simultaneously (a biplot), and variances (a screeplot, where the log of the explained variance is plotted for each PC).

Usage

## S3 method for class 'PCA'
scoreplot(object, pc = c(1, 2), pcscores = scores(object),
          show.names = FALSE, xlab, ylab, xlim, ylim, ...)
## S3 method for class 'PCA'
loadingplot(object, pc = c(1, 2), pcloadings = loadings(object),
            scalefactor = 1, add = FALSE, show.names = FALSE,
            xlab, ylab, xlim, ylim, col = "blue", min.length =
            0.01, varnames = NULL, ...)
## S3 method for class 'PCA'
biplot(x, pc = c(1,2),
        show.names = c("none", "scores", "loadings", "both"),
        score.col = 1, loading.col = "blue",
        min.length = .01, varnames = NULL, ...)
screeplot(object, type = c("scree", "percentage"), npc, ...)

Arguments

x, object	an object of class "PCA" (see below).
pc	which PCs to show.
pcscores	matrix of scores, by default the scores of the PCA model object.
show.names	show names rather than plotting symbols. For loadingplot and scoreplot a logical (default: FALSE), for biplot one of 'scores', 'loadings', 'both' or 'none' (default).
xlab, ylab, xlim, ylim, col	graphical parameters of the plot.
pcloadings	matrix of loadings, by default the loadings of the PCA model object.
scalefactor	scaling factor for the loadings; used internally, when the loadingplot function is called from within biplot.PCA.
add	logical, whether to add to the existing plot (again, useful when loadingplot is called from within biplot.PCA).
npc	how many PCs to show in the scree plot (starting from 1).
type	show a real screeplot (scree) or show the percentage of variance explained (percentage).
score.col, loading.col	colours of the scores and loadings in a biplot.
min.length	minimal length of loading vectors to be plotted by arrows. Vectors that are too short lead to warning messages, are not interesting, and only clutter the graphic.
varnames	alternative vector of variable names.
...	Graphical arguments passed on to lower-level plotting functions.

Details

Score plots and loading plots show the amount of explained variance at the axis labels only when PCA has been performed at mean-centered data.

Author(s)

Ron Wehrens

References

R. Wehrens. "Chemometrics with R - Multivariate Data Analysis in the Natural Sciences and Life Sciences". Springer, Heidelberg, 2011.

See Also

PCA

Examples

data(wines, package = "kohonen")
wines.PC <- PCA(scale(wines))
wine.classes <- as.integer(vintages)
scoreplot(wines.PC, col = wine.classes, pch = wine.classes)
loadingplot(wines.PC, show.names = TRUE)
biplot(wines.PC, score.col = wine.classes)
screeplot(wines.PC)

Example output

Attaching package: 'ChemometricsWithR'

The following objects are masked from 'package:stats':

    loadings, screeplot

ChemometricsWithR documentation built on May 2, 2019, 10:25 a.m.