RobStatTM: prcompRob – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

prcompRob

Robust Principal Components Cont'd

Description

This function uses the pcaRobS function to compute all principal components while behaving similarly to the prcomp function

Usage

prcompRob(x, rank. = NULL, delta.scale = 0.5, max.iter = 100L)

Arguments

`x`	data matrix with observations in rows
`rank.`	Maximal number of principal components to be used (optional)
`delta.scale`	"delta" parametor of the scale M-estimator (default = 0.5)
`max.iter`	maximum number of iterations (default = 100)

Value

`sdev`	the standard deviation of the principal components
`rotation`	matrix containing the factor loadings
`x`	matrix containing the rotated data
`center`	the centering used

Author(s)

Gregory Brownson, gregory.brownson@gmail.com

Examples

data(wine)

p.wine <- prcompRob(wine)
summary(p.wine)

## Choose only 5
p5.wine <- prcompRob(wine, rank. = 5)
summary(p5.wine)

RobStatTM

Robust Statistics: Theory and Methods

v1.0.2

GPL (>= 3)

Authors

Matias Salibian-Barrera [cre], Victor Yohai [aut], Ricardo Maronna [aut], Doug Martin [aut], Gregory Brownson [aut] (ShinyUI), Kjell Konis [aut], Kjell Konis [cph] (erfi), Christophe Croux [ctb] (WBYlogreg, BYlogreg), Gentiane Haesbroeck [ctb] (WBYlogreg, BYlogreg), Martin Maechler [cph] (lmrob.fit, lmrob..M..fit, lmrob.S), Manuel Koller [cph] (lmrob.fit, .vcov.avar1, lmrob.S, lmrob.lar), Matias Salibian-Barrera [aut]

Initial release

2020-03-02