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Biometrika 1988 75(4):651-659; doi:10.1093/biomet/75.4.651
© 1988 by Biometrika Trust
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A Bayesian approach to outlier detection and residual analysis

KATHRYN CHALONER and ROLLIN BRANT

Department of Applied Statistics, University of Minnesota St. Paul, Minnesota 55108, U.S.A.
Department of Preventive Medicine and Biostatistics, University of Toronto Toronto M5S 1A8, Canada

An approach to detecting outliers in a linear model is developed. An outlier is defined to be an observation with a large random error, generated by the linear model under consideration. Outliers are detected by examining the posterior distribution of the random errors. An augmented residual plot is also suggested as a graphical aid in finding outliers.

Key Words: Leverage • Linear model • Posterior distribution • Residual plot


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