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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)
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)
the standard deviation of the principal components
matrix containing the factor loadings
matrix containing the rotated data
the centering used
# NOT RUN { 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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