USING KULLBACK-LEIBLER DISTANCE FOR PERFORMANCE EVALUATION OF SEARCH DESIGNS

This paper considers the search problem, introduced by Srivastava [10]. This is a model discrimination problem. In the context of search linear models, discrimination ability of search designs has been studied by several researchers. Some criteria have been developed to measure this capability, however, they are restricted in a sense of being able to work for searching only one possible nonzero effect. In this paper, two criteria are proposed, based on Kullback-Leibler distance. These criteria are able to evaluate the search ability of designs, without any restriction on the number of nonzero effects.