Abdolreza Sayareh, Parisa Torkman,
Volume 3, Issue 1 (9-2009)
Abstract
Model selection aims to find the best model. Selection in the presence of censored data arises in a variety of problems. In this paper we emphasize that the Kullback-Leibler divergence under complete data has a better advantage. Some procedures are provided to construct a tracking interval for the expected difference of Kullback-Leibler risks based on Type II right censored data. Simulation study shows that this procedure works properly for optimum model selection.
