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Credibility Weighted Hazard Estimation

Published online by Cambridge University Press:  29 August 2014

Jens Perch Nielsen*
Affiliation:
Codan
Bjørn Lunding Sandqvist*
Affiliation:
Codan
*
Codan, Gammel Kongevej 60, 1790 København V, Denmark, E-mail:[email protected]& [email protected]
Codan, Gammel Kongevej 60, 1790 København V, Denmark, E-mail:[email protected]& [email protected]
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Abstract

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Credibility weighting is helpful in many insurance applications where sparse data crave information from other sources of data. In this paper we aim at estimating a hazard curve using the nonparametric kernel method, where a credibility weighting principle is used locally, so that areas of sparse data for one subgroup can be alleviated by available information from other subgroups. The credibility estimator is found through a Hilbert space projection formulation of Buhlmann-Straub's credibility approach.

Type
Workshop
Copyright
Copyright © International Actuarial Association 2000

References

Andersen, P.K., Borgan, Ø., Gill, R.D., and Keiding, N. (1992) Statistical models based on counting processes. Springer-Verlag, New-York.Google Scholar
Bühlmann, H. and Straub, E. (1970) Glaubwürdigkeit für Schadensätze. Bulletin of the Association of Swiss Actuaries 70, 111133.Google Scholar
Hardy, M.R. and Panjer, H.H. (1998) A credibility approach to mortality risk. ASTIN Bulletin 28, 269283.CrossRefGoogle Scholar
Hjort, N.L. (1990) Nonparametric Bayes estimators based on beta processes in models for life history data. Ann. Statist. 18, 12591294.CrossRefGoogle Scholar
Hjort, N.L. (1992) Semiparametric estimation of parametric hazard rates. In Klein, J.P. and Goel, P.K., eds., Survival Analysis: State of the Art, pp. 211236, Kluwer, Dordrecht.CrossRefGoogle Scholar
Ramlau-Hansen, H. (1983) Smoothing counting process intensities by means of kernel functions. Ann. Statist. 11, 453466.CrossRefGoogle Scholar
Young, V.R. (1997) Credibility using semiparametric models. ASTIN Bulletin 27, 273285.CrossRefGoogle Scholar
Young, V.R. (1998) Robust Baysian credibility using semiparametric models. ASTIN Bulletin 28, 187203.CrossRefGoogle Scholar