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Statistiques des valeurs extrêmes dans le cas de lois discrètes

  • Borchani, Anis

    ()

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

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    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

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    File URL: http://hal-essec.archives-ouvertes.fr/docs/00/57/25/59/PDF/10009.pdf
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    Paper provided by ESSEC Research Center, ESSEC Business School in its series ESSEC Working Papers with number DR 10009.

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    Length: 88 pages
    Date of creation: Dec 2010
    Date of revision:
    Handle: RePEc:ebg:essewp:dr-10009
    Contact details of provider: Postal: ESSEC Research Center, BP 105, 95021 Cergy, France
    Web page: http://www.essec.edu/
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