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An empirical Bayes approach to outliers
Authors:Enrique de Alba  John Van Ryzin
Affiliation: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).
Keywords:Primary 62C99  62F05  Empirical Bayes Procedures  Detection of Outliers  Average Risk Asymptotic Optimality  Rates of Convergence
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