A short comment on the paper “A simple method to estimate parametric claim size distributions from grouped data”, by Brix, J. and Pfeifer, D.
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Conclusion
We conclude that fitting a GPD over the threshold value u=20000 and estimating its parameters by means of thex 2-method is not as poor as claimed in Brix and Pfeifer [1]. It seems that the EVT based approach provides even better estimates than the method proposed in [1] when modeling extreme tail events, see the values n1 and the corresponding values KI_NEW for u1≥ 100000 onwards. We also believe that there is no major drawback when using estimation techniques which incorporate the cummulative distribution function rather than the density function. In case the cumulative distribution functions should not be implemented in a (statistical) software package, one can easily get around this problem by applying standard numerical integration techniques.
Keywords
Moment Problem Generalize Pareto Distribution Extreme Value Theory Health Care Data Density Base MethodPreview
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References
- [1]Brix, J., andPfeifer, D. A simple method to estimate parametric claim size distributions from grouped data.Blätter der Deutschen Gesellschaft für Versicherungsmathematik, Band XXIV, Heft 3 (2000), 495–505.Google Scholar
- [2]Furrer, H. J. Methoden der Extremwerttheorie zur Bestimmung eines Einzelschaden-Exzedenten im Krankenversicherungsbereich.Blätter der Deutschen Gesellschaft für Versicherungsmathematik, Band XXIV, Heft 1 (1999), 87–102.Google Scholar