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Linear Bayes Estimation in Finite Populations with a Categorical Auxiliary Variable

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Cocchi, Daniela [University of Bologna] Mouchart, Michel [UCL]

Least squares approximations are given for both the structural expectation and the unsampled population values in a finite population model with an auxiliary variable which is categorical. An ANOVA model is used as a guideline and a motivation. The linear BAYES approach is shown to provide an easy and operational solution to the well known difficulty of integrating out the superpopulation parameters in a BAYESian framework.

Document type Article de périodique (Journal article) – Article de recherche
Publication date 1990
Language Anglais
Journal information "Statistics : a journal of theoretical and applied statistics" - Vol. 21, no.3, p. 437-454 (1990)
Peer reviewed yes
Publisher Taylor & Francis Ltd. ((United Kingdom) Abingdon)
issn 0233-1888
e-issn 1029-4910
Publication status Publié
Affiliation UCL - EUEN/CORE - Center for operations research and econometrics
Keywords Least squares approximations ; linear BAYES method ; finite population ; Partial exchangeability ; superpopulation
Links
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Bibliographic reference Cocchi, Daniela ; Mouchart, Michel. Linear Bayes Estimation in Finite Populations with a Categorical Auxiliary Variable. In: Statistics : a journal of theoretical and applied statistics, Vol. 21, no.3, p. 437-454 (1990)
Permanent URL http://hdl.handle.net/2078.1/125383