Bayesian checking of the second levels of hierarchical models
Bayesian checking of the second levels of hierarchical models
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DOI：
10.1214/07-sts235
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发表时间：
2007-08-01
影响因子：
5.7
通讯作者：
Castellanos, M. E.
中科院分区：
文献类型：
--
作者：
Bayarri, M. J.;Castellanos, M. E.
分层模型越来越多地用于许多应用中。沿着这种增加的使用而来的是调查模型是否与观察到的数据兼容的期望。贝叶斯方法非常适合消除这些复杂模型中的许多（滋扰）参数，在本文中，我们研究贝叶斯模型检验方法。由于我们考虑模型检查作为一个初步的，探索性的分析，我们专注于客观的贝叶斯方法，其中仔细规范的信息先验分布是避免的。许多例子，并给出了不同的建议进行了调查和批判性的比较。
Hierarchical models are increasingly used in many applications. Along with this increased use comes a desire to investigate whether the model is compatible with the observed data. Bayesian methods are well suited to eliminate the many (nuisance) parameters in these complicated models; in this paper we investigate Bayesian methods for model checking. Since we contemplate model checking as a preliminary, exploratory analysis, we concentrate on objective Bayesian methods in which careful specification of an informative prior distribution is avoided. Numerous examples are given and different proposals are investigated and critically compared.