کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
416713 | 681398 | 2006 | 20 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
MCMC methods to approximate conditional predictive distributions
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
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چکیده انگلیسی
Sampling from conditional distributions is a problem often encountered in statistics when inferences are based on conditional distributions which are not of closed-form. Several Markov chain Monte Carlo (MCMC) algorithms to simulate from them are proposed. Potential problems are pointed out and some suitable modifications are suggested. Approximations based on conditioning sets are also explored. The issues are illustrated within a specific statistical tool for Bayesian model checking, and compared in an example. An example in frequentist conditional testing is also given.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 51, Issue 2, 15 November 2006, Pages 621–640
Journal: Computational Statistics & Data Analysis - Volume 51, Issue 2, 15 November 2006, Pages 621–640
نویسندگان
M.J. Bayarri, M.E. Castellanos, J. Morales,