Articles | Volume 15, issue 8
https://doi.org/10.5194/nhess-15-1757-2015
https://doi.org/10.5194/nhess-15-1757-2015
Brief communication
 | 
11 Aug 2015
Brief communication |  | 11 Aug 2015

Statistical detection and modeling of the over-dispersion of winter storm occurrence

M. Raschke

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Cited articles

Claeskens, G. and Hjort, N. L.: Model selection and model averaging, in: Cambridge Series in Statistical and Probabilistic Mathematics, Cambridge University Press, Cambridge, 2008.
Coles, S.: An introduction to statistical modeling of extreme values, Springer, London, 2001.
Consul, P. C. and Jain, G. C.: A generalization of the Poisson distribution, Technometrics, 15, 791–799, 1973.
Consul, P. C. and Shoukri, M. M.: Maximum likelihood estimation for the generalized Poisson distribution, Commun. Stat. Theory Meth., 10, 977–991, 1984.
Fahrmeir, L., Kneib, T., Lang, S., and Marx, B.: Regression – models, methods and applications, Springer, Heidelberg, Germany, 2013.
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Short summary
Here, I discuss and improve the detection and modeling of the over-dispersion of winter storm occurrence using the example of Germany. For this purpose, the generalized Poisson distribution and criteria for the model selection are introduced. Correct statistical model selection ensures the statistical significance of the model, including an over-dispersion. The relation between expectation and variance of a thinned inhomogeneous Poisson process is derived. This is also applied to data.
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