Predictive View of the Detection of Influential Observations in GMANOVA

摘要

The detection of influential subsets of observations (possibly outliers) under the GMANOVA model is considered according to a technique with fairly discerning capabilities. Kullback-Leibler divergences are used to measure the discrepancy between two predictive densities, the one based on the complete data set and the other on a subset of the data set.