Semiparametric estimation for space-time max-stable processes: F -madogram-based estimation approach

Abstract : Max-stable processes have been expanded to quantify extremal dependence in spatio-temporal data. Due to the interaction between space and time, spatio-temporal data are often complex to analyze. So, characterizing these dependencies is one of the crucial challenges in this field of statistics. This paper suggests a semiparametric inference methodology based on the spatio-temporal F-madogram for estimating the parameters of a space-time max-stable process using gridded data. The performance of the method is investigated through various simulation studies. Finally, we apply our inferential procedure to quantify the extremal behavior of radar rainfall data in a region in the State of Florida.
Complete list of metadatas
Contributor : Véronique Maume-Deschamps <>
Submitted on : Saturday, May 18, 2019 - 6:29:55 PM
Last modification on : Thursday, June 13, 2019 - 11:42:45 AM


Semiparametric estimation_hal....
Files produced by the author(s)


  • HAL Id : hal-02133500, version 1
  • ARXIV : 1905.07912


Abdul-Fattah Abu-Awwad, Véronique Maume-Deschamps, Pierre Ribereau. Semiparametric estimation for space-time max-stable processes: F -madogram-based estimation approach. 2019. ⟨hal-02133500⟩



Record views


Files downloads