Estimation of Structural Parameters in Crossed Classification Credibility Model Using Linear Mixed Models

Wing K. Fung () and Xiaochen Xu
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Wing K. Fung: The University of Hong Kong, Department of Statistics and Actuarial Science
Xiaochen Xu: The University of Hong Kong, Department of Statistics and Actuarial Science

A chapter in COMPSTAT 2008, 2008, pp 241-251 from Springer

Abstract: Abstract In this paper, the linear mixed model is used under the Dannenburg’s two-way crossed classification model. Maximum likelihood (ML) and restricted maximum likelihood (REML) methods are employed to estimate the structural parameters with both independent and exchangeable error structures. Evidenced by results of simulation studies, the proposed linear mixed effects estimators appear to outperform those given by Dannenburg with both independent and exchangeable error structures.

Keywords: linear mixed model; crossed classification credibility model; maximum likelihood estimator; restricted maximum likelihood estimator; SAS (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2084-3_20

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DOI: 10.1007/978-3-7908-2084-3_20

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