Back To Index Previous Article Next Article Full Text


Statistica Sinica 4(1994), 715-727


A NEW TECHNIQUE FOR IMPROVED CONFIDENCE

BOUNDS FOR THE PROBABILITY OF CORRECT

SELECTION


Shanti S. Gupta, Yuning Liao, Chunfu Qiu and Jin Wang


Purdue University, New Drug Services Inc., University of Illinois
and Purdue University


Abstract: This paper deals with the problem of estimating the probability of a correct selection (PCS) in location parameter models. Practical lower confidence bounds for the PCS in location parameter models are presented with a user's choice of dimension q(1<=q<=k-1) for computation, where k is the number of populations. It is shown that the larger the q, the better the lower bound, but the more complicated the computation. The result when q=1 coincides with Kim's (1986) result. A numerical example is presented to show that our lower bound with q=2 improves Kim's result considerably. With an appropriate modification, our result can be applied to location-scale parameter models with the scale parameter unknown.



Key words and phrases: Ranking and selection, probability of a correct selection, confidence region, location parameter.



Back To Index Previous Article Next Article Full Text