pca.distances: Compute score and orthogonal distances for Principal Components (objects of class 'Pca')
Description
Compute score and orthogonal distances for an object (derived from)Pca-class.
Usage
pca.distances(obj, data, r, crit=0.975)
Value
An S4 object of class derived from the virtual class Pca-class -
the same object passed to the function, but with the score and orthogonal
distances as well as their cutoff values and the corresponding flags appended to it.
Arguments
obj
an object of class (derived from) "Pca".
data
The data matrix for which the "Pca" object was computed.
This function calculates the score and orthogonal distances and the
appropriate cutoff values for identifying outlying observations.
The computed values are used to
create a vector a of flags, one for each observation, identifying the outliers.
References
M. Hubert, P. J. Rousseeuw, K. Vanden Branden (2005), ROBPCA: a new
approach to robust principal components analysis, Technometrics, 47, 64--79.
Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis.
Journal of Statistical Software, 32(3), 1--47.
tools:::Rd_expr_doi("10.18637/jss.v032.i03").