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Biometrika 1986 73(3):533-541; doi:10.1093/biomet/73.3.533
© 1986 by Biometrika Trust
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Masking unmasked

A. C. ATKINSON

Department of Mathematics, Imperial College London SW7 2BZ, U.K.

Diagnostic methods based on the deletion of single observations are well established in multiple regression analysis. Multiple deletion methods are also well developed, but are little applied due to combinatorial problems. But sometimes the pattern of multiple outliers cannot be revealed by single deletion methods. In such cases ‘masking’ is said to occur. The method of unmasking described in the paper uses samples of elemental sets of the observations to fit least median of squares regression to the data. This robust method has high resistance and serves as an exploratory tool for the identification of outliers. The techniques of multiple deletion regression diagnostics are then directly applicable for confirmation of the presence of outliers and influential observations.

Key Words: Cook's distance • Elemental sets • Least median of squares regression • Masking • Multiple deletion • Outlire • Prediction residual • Random search • Regression diagnostic • Robust regression • Unmasking


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