2007/08/01 by M. J. Bayarri, M. E. Castellanos · 8 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #Statistical Methods and Bayesian Inference #stat.ME
paper · pdf · doi:10.1214/07-sts235
published as Statistical Science 2007, Vol. 22, No. 3, 322-343 · This paper commented in: [arXiv:0802.0746], [arXiv:0802.0747], [arXiv:0802.0749], [arXiv:0802.0752]. Rejoinder in [arXiv:0802.0754]. Published in at http://dx.doi.org/10.1214/07-STS235 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)
openalex publication_date 2007/08/01 · arxiv created 2008/02/06 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
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.