Dept. de Estadistica y Matemáticas, ITAM, Río Hondo #1, San Angel, 20 DF, México;Division of Biostatistics and Dept. of Mathematical Statistics, Columbia University, New York, NY 10032, USA
Abstract:
A formulation of the problem of detecting outliers as an empirical Bayes problem is studied. In so doing we encounter a non-standard empirical Bayes problem for which the notion of average risk asymptotic optimality (a.r.a.o.) of procedures is defined. Some general theorems giving sufficient conditions for a.r.a.o. procedures are developed. These general results are then used in various formulations of the outlier problem for underlying normal distributions to give a.r.a.o. empirical Bayes procedures. Rates of convergence results are also given using the methods of Johns and Van Ryzin (1971, 1972).