Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Credibility estimation via kernel mixed effects model

  • Shim, Joo-Yong (Department of Applied Statistics, Catholic University of Daegu) ;
  • Kim, Tae-Yoon (Department of Statistics, Keimyung University) ;
  • Lee, Sang-Yeol (Department of Statistics, Seoul National University) ;
  • Hwa, Chang-Ha (Department of Statistics, Dankook University)
  • Published : 2009.03.31
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Abstract

Credibility models are actuarial tools to distribute premiums fairly among a heterogeneous group of policyholders. Many existing credibility models can be expressed as special cases of linear mixed effects models. In this paper we propose a nonlinear credibility regression model by reforming the linear mixed effects model through kernel machine. The proposed model can be seen as prediction method applicable in any setting where repeated measures are made for subjects with different risk levels. Experimental results are then presented which indicate the performance of the proposed estimating procedure.

Keywords

References

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