a Department of Statistics, Purdue University, W. Lafayette, IN 47907-1399, USA
b Department of Probability and Statistics, Beijing University, Beijing 100871, People's Republic of China
Abstract:
We investigate the problem of selecting the best population from positive exponential family distributions based on type-I censored data. A Bayes rule is derived and a monotone property of the Bayes selection rule is obtained. Following that property, we propose an early selection rule. Through this early selection rule, one can terminate the experiment on a few populations early and possibly make the final decision before the censoring time. An example is provided in the final part to illustrate the use of the early selection rule.