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Linear Filtering and Recursive Credibility Estimation

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  • Zehnwirth, Ben

Abstract

Recursive credibility estimation is discussed from the viewpoint of linear filtering theory. A conjunction of geometric interpretation and the innovation approach leads to general algorithms not developed before. Moreover, covariance characterizations considered by other researchers drop our elegantly as a result of geometric considerations. Examples are presented of Kalman type filters valid for non-Gaussian measurements.

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  • Zehnwirth, Ben, 1985. "Linear Filtering and Recursive Credibility Estimation," ASTIN Bulletin, Cambridge University Press, vol. 15(1), pages 19-35, April.
    • Handle: RePEc:cup:astinb:v:15:y:1985:i:01:p:19-35_00
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    Cited by:

    1. Asamoah, Kwadwo, 2016. "On the credibility of insurance claim frequency: Generalized count models and parametric estimators," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 339-353.
    2. Martin Englund & Jim Gustafsson & Jens Perch Nielsen & Fredrik Thuring, 2009. "Multidimensional Credibility With Time Effects: An Application to Commercial Business Lines," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(2), pages 443-453, June.
    3. Helena Jasiulewicz, 2013. "Przestrzeń stanów i filtr Kalmana w teorii ubezpieczeń," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 31, pages 101-116.

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