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Statistiques des valeurs extrêmes dans le cas de lois discrètes

Author

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  • Borchani, Anis

    (ESSAI (Ecole Supérieure de la Statistique et de l’Analyse de l’Informatio), Tunis)

Abstract

We propose a method to generate a warning system for the early detection of time clusters in discrete time series. Two approaches are developed, one using an approximation of the return period of an extreme event, independently of the nature of the data, the other using an estimation of the return period via standard EVT tools after a smoothing of our discrete data into continuous ones. This method allows us to define a surveillance and prediction system which is applied to finance and public health surveillance

Suggested Citation

  • Borchani, Anis, 2010. "Statistiques des valeurs extrêmes dans le cas de lois discrètes," ESSEC Working Papers DR 10009, ESSEC Research Center, ESSEC Business School.
    • Handle: RePEc:ebg:essewp:dr-10009
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    Keywords

    applications in insurance and finance; clusters; epidemiology; Extreme Value Theory; extreme quantile; outbreak detection; return level; return period; surveillance;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • I10 - Health, Education, and Welfare - - Health - - - General

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