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  • 标题:A design-based approximation to the Bayes Information Criterion in finite population sampling
  • 本地全文:下载
  • 作者:Enrico Fabrizi ; Parthasarathi Lahiri
  • 期刊名称:Statistica
  • 印刷版ISSN:1973-2201
  • 出版年度:2013
  • 卷号:73
  • 期号:3
  • 页码:289-301
  • DOI:10.6092/issn.1973-2201/4325
  • 语种:English
  • 出版社:Dep. of Statistical Sciences "Paolo Fortunati", Università di Bologna
  • 摘要:In this article, various issues related to the implementation of the usual Bayesian Information Criterion (BIC) are critically examined in the context of modelling a finite population. A suitable design-based approximation to the BIC is proposed in order to avoid the derivation of the exact likelihood of the sample which is often very complex in a finite population sampling. The approximation is justified using a theoretical argument and a Monte Carlo simulation study.
  • 关键词:Bayes factor;Hypothesis testing;Model selection;Pseudo-maximumlikelihood;Cluster sampling
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