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Estimating the Difference of Kullback-Leibler Risks under Type II Right Censored Data for Non-Nested Models
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Abdolreza Sayareh *   , Parisa Torkman |
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Abstract: (23433 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. |
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| Keywords: Akaike Criterion, Kullback-Leibler, Type II Right Censored Data. |
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Full-Text [PDF 489 kb]
(4785 Downloads)
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Type of Study: Research |
Subject:
Statistical Inference
Received: 2011/07/4 | Accepted: 2013/08/13 | Published: 2020/02/18
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