prcompRob: Robust Principal Components Cont'd

In msalibian/RobStatTM: Robust Statistics: Theory and Methods

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, [e-mail]

Examples

data(wine)

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

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

msalibian/RobStatTM documentation built on April 24, 2024, 5:10 a.m.