Finding multivariate outliers with FastPCS

Authors:
Kaveh Vakili;Eric Schmitt
Affiliations:
-;-
Venue:
Computational Statistics & Data Analysis
Year:
2014

Citing 3
Cited 0

Robust regression and outlier detection

Robust regression and outlier detection
A fast algorithm for the minimum covariance determinant estimator

Technometrics
Lattice: Multivariate Data Visualization with R

Lattice: Multivariate Data Visualization with R

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Abstract

The Projection Congruent Subset (PCS) is a new method for finding multivariate outliers. Like many other outlier detection procedures, PCS searches for a subset which minimizes a criterion. The difference is that the new criterion was designed to be insensitive to the outliers. PCS is supported by FastPCS, a fast and affine equivariant algorithm which is also detailed. Both an extensive simulation study and a real data application from the field of engineering show that FastPCS performs better than its competitors.