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Abstract Details
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Activity Number:
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400
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #302218 |
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Title:
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Bayesian Predictive Inference For Finite Population Quantities Under Informative Sampling
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Author(s):
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Junheng Ma*+
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Companies:
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Statistical and Applied Mathematical Sciences Institute
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Address:
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19 T.W. Alexander Drive, Research Triangle Park, NC, 27709,
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Keywords:
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Bayesian predictive inference ;
finite population ;
informative sampling
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Abstract:
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Bayesian predictive inference is investigated for finite population quantities under informative sampling, i.e., unequal selection probabilities. Only limited information about the sample design is available, i.e., only the first-order selection probabilities corresponding to the sampled units are known. We have developed a full Bayesian approach to make inference for the parameters of the finite population and also predictive inference for the non-sampled units. Thus we can make inference for any characteristic of the finite population quantities. In addition, our methodology, using Markov chain Monte Carlo, avoids the necessity of using asymptotic approximations.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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