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Activity Number:
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509
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Type:
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Contributed
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Date/Time:
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Thursday, August 2, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #309960 |
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Title:
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Bayesian Analysis of Progressively Type-II Censored Sample from Burr Type-XII Distribution
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Author(s):
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Younshik Chung*+ and Seongho Song and Chansoo Kim and Junghoon Jang
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Companies:
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Pusan National University and University of Cincinnati and Kongju National University and Korea Food and Drug Association
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Address:
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30 Jangjun Dong Guemjung Gu, Busan, Republic of, Republic of Korea
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Keywords:
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Progressively Type-II Censored sample ; Burr Type-XII distribution ; Expected Fisher Information ; Bayesian Estimation ; Bayesian Prediction
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Abstract:
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In this article, the estimation of parameters based on a progressively Type-II censored sample from a Burr Type-XII distribution is investigated by using maximum likelihood (ML) approach as well as Bayesian approach. The exact expression of the expected Fisher information matrix of parameters in the distribution has been obtained. Based on this result, we construct the confidence interval for the parameters using the asymptotic normality of the ML estimator. We compare it to Bayesian credible interval. We also consider the problem of predicting an independent future observation from the same distribution. The Gibbs and Metropolis samplers are used to predict the behavior of future observations from the same distribution.
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