Empirical Bayes Testing with Exponential Random Right Censoring

摘要

This paper investigates empirical Bayes tests for exponential distributions based on exponentially randomly right censored data. By mimicking the behavior of a Bayes test, an empirical Bayes test δ_n~* is constructed. The regret of δ_n~* is used as a measure of its performance. It has been shown that under very mild conditions, the empirical Bayes test δ_n~* is asymptotically optimal, and its regret converges to zero at a rate O(n~(-1)(lnn)~2), where n is the number of past data available when the present decision problem is considered.