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Robust Credibility via Robust Kalman Filtering

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  • Kremer, Erhard

Abstract

Credibility theory is closely related to Kalman filtering. As a consequence, methods proposed for robustifying the Kalman filter can often be specialised to obtain robust credibility rating procedures. The application of one such method to several classical credibility models is shown in this paper.

Suggested Citation

  • Kremer, Erhard, 1994. "Robust Credibility via Robust Kalman Filtering," ASTIN Bulletin, Cambridge University Press, vol. 24(2), pages 221-233, November.
    • Handle: RePEc:cup:astinb:v:24:y:1994:i:02:p:221-233_00
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    Cited by:

    1. Agustin Hernandez Bastida & Emilio Gomez Deniz & Jose Maria Perez Sanchez, 2009. "Bayesian robustness of the compound Poisson distribution under bidimensional prior: an application to the collective risk model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(8), pages 853-869.
    2. Pitselis, Georgios, 2004. "A seemingly unrelated regression model in a credibility framework," Insurance: Mathematics and Economics, Elsevier, vol. 34(1), pages 37-54, February.
    3. Garrido, José & Romera, Rosario, 1995. "On credibility and robustness with the Kalman filter," DES - Working Papers. Statistics and Econometrics. WS 4509, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. 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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