pca.scoreplot: Score plot for Principal Components (objects of class 'Pca')

In armstrtw/rrcov: Scalable Robust Estimators with High Breakdown Point

Description

Produces a score plot from an object (derived from) Pca-class.

Usage

    pca.scoreplot(obj, i=1, j=2, main, id.n=0, ...)

Arguments

obj	an object of class (derived from) "Pca".
i	First score coordinate, defaults to i=1.
j	Second score coordinate, defaults to j=2.
main	The main title of the plot.
id.n	Number of observations to identify by a label. Defaults to id.n=0.
...	optional arguments to be passed to the internal graphical functions.

Author(s)

Valentin Todorov [e-mail]

See Also

Pca-class, PcaClassic, PcaRobust-class.

Examples

require(graphics)

## PCA of the Hawkins Bradu Kass's Artificial Data
##  using all 4 variables
data(hbk)
pca <- PcaHubert(hbk)
pca
pca.scoreplot(pca)

armstrtw/rrcov documentation built on May 10, 2019, 1:43 p.m.