Bayesian approach to outlier detection in multivariate normal samples and linear models

Abstract

Chaloner and Brant (1988) propose a Bayesian method for identifying outliers in univariate linear models. This paper presents an approach generalizing their idea to multivariate normal samples and multivariate linear models. The posterior distribution of the squared norm of the realized errors is used f o loutlier identification. Bayes factors are used for examining whether or not an observation is an outlier.