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This function uses the pcaRobS function to compute all principal components while behaving similarly to the prcomp function
prcompRob(x, rank. = NULL, delta.scale = 0.5, max.iter = 100L)
the standard deviation of the principal components
matrix containing the factor loadings
matrix containing the rotated data
the centering used
data matrix with observations in rows
Maximal number of principal components to be used (optional)
"delta" parametor of the scale M-estimator (default = 0.5)
maximum number of iterations (default = 100)
Gregory Brownson, gregory.brownson@gmail.com
data(wine) p.wine <- prcompRob(wine) summary(p.wine) ## Choose only 5 p5.wine <- prcompRob(wine, rank. = 5) summary(p5.wine)
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