Composite Likelihood Bayesian Information Criteria for Model Selection in High-Dimensional Data
نویسندگان
چکیده
منابع مشابه
Composite Likelihood Bayesian Information Criteria for Model Selection in High-Dimensional Data
For high-dimensional data sets with complicated dependency structures, the full likelihood approach often leads to intractable computational complexity. This imposes difficulty on model selection, given that most traditionally used information criteria require evaluation of the full likelihood. We propose a composite likelihood version of the Bayes information criterion (BIC) and establish its ...
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ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2010
ISSN: 0162-1459,1537-274X
DOI: 10.1198/jasa.2010.tm09414