کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
415989 681266 2010 20 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Default Bayesian model determination methods for generalised linear mixed models
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Default Bayesian model determination methods for generalised linear mixed models
چکیده انگلیسی

A default strategy for fully Bayesian model determination for generalised linear mixed models (GLMMs) is considered which addresses the two key issues of default prior specification and computation. In particular, the concept of unit-information priors is extended to the parameters of a GLMM. A combination of Markov chain Monte Carlo (MCMC) and Laplace approximations is used to compute approximations to the posterior model probabilities to find a subset of models with high posterior model probability. Bridge sampling is then used on the models in this subset to approximate the posterior model probabilities more accurately. The strategy is applied to four examples.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 54, Issue 12, 1 December 2010, Pages 3269–3288
نویسندگان
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