کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
481086 1446116 2010 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Merging experts’ opinions: A Bayesian hierarchical model with mixture of prior distributions
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
Merging experts’ opinions: A Bayesian hierarchical model with mixture of prior distributions
چکیده انگلیسی

In this paper, a general approach is proposed to address a full Bayesian analysis for the class of quadratic natural exponential families in the presence of several expert sources of prior information. By expressing the opinion of each expert as a conjugate prior distribution, a mixture model is used by the decision maker to arrive at a consensus of the sources. A hyperprior distribution on the mixing parameters is considered and a procedure based on the expected Kullback–Leibler divergence is proposed to analytically calculate the hyperparameter values. Next, the experts’ prior beliefs are calibrated with respect to the combined posterior belief over the quantity of interest by using expected Kullback–Leibler divergences, which are estimated with a computationally low-cost method. Finally, it is remarkable that the proposed approach can be easily applied in practice, as it is shown with an application.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Operational Research - Volume 207, Issue 1, 16 November 2010, Pages 284–289
نویسندگان
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