A design-based approximation to the Bayes Information Criterion in finite population sampling

Autor:	Enrico Fabrizi, Parthasarathi Lahiri
Jazyk:	angličtina
Rok vydání:	2014
Předmět:	Bayes factor Hypothesis testing Model selection Pseudo-maximumlikelihood Cluster sampling Statistics HA1-4737
Zdroj:	Statistica, Vol 73, Iss 3, Pp 289-301 (2014)
Druh dokumentu:	article
ISSN:	0390-590X 1973-2201
DOI:	10.6092/issn.1973-2201/4325
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/1592dd36c9364dc698d3d6c517608fef Zobrazit plný text záznamu View record in DOAJ