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:: Volume 3, Issue 1 (9-2009) ::
JSS 2009, 3(1): 59-78 Back to browse issues page
Estimating the Difference of Kullback-Leibler Risks under Type II Right Censored Data for Non-Nested Models
Abdolreza Sayareh * , Parisa Torkman
Abstract:   (22259 Views)
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.
Keywords: Akaike Criterion, Kullback-Leibler, Type II Right Censored Data.
Full-Text [PDF 489 kb]   (4253 Downloads)    
Type of Study: Research | Subject: Statistical Inference
Received: 2011/07/4 | Accepted: 2013/08/13 | Published: 2020/02/18
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Sayareh A, Torkman P. Estimating the Difference of Kullback-Leibler Risks under Type II Right Censored Data for Non-Nested Models. JSS 2009; 3 (1) :59-78
URL: http://jss.irstat.ir/article-1-30-en.html


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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 3, Issue 1 (9-2009) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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