Forthcoming

A Semi-parametric Estimation for Max-mixture Spatial Process

Accepted August 2025

Authors

  • Manaf Ahmed University of Mosul
  • Véronique Maume-Deschamps Université Claude Bernard Lyon 1
  • Pierre Ribereau Université Claude Bernard Lyon 1

Keywords:

spatial dependence measure, asymptotic dependence/independence, max-stable process, max-mixture process

Abstract

We propose a semi-parametric estimation procedure in order to estimate the parameters of a max-mixture model as an alternative to composite likelihood estimation. This procedure uses the F-madogram. We propose to minimize the square difference between the theoretical F-madogram and an empirical one. We evaluate the performance of this estimator through a simulation study and we compare our method to composite likelihood estimation. We apply our estimation procedure to daily rainfall data from East Australia.

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Published

2025-08-30

Issue

new article

Section

Forthcoming Paper

License

Copyright (c) 2025 REVSTAT-Statistical Journal

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Ahmed, M., Maume-Deschamps, V. ., & Ribereau, P. (2025). A Semi-parametric Estimation for Max-mixture Spatial Process: Accepted August 2025. REVSTAT-Statistical Journal. https://revstat.ine.pt/index.php/REVSTAT/article/view/870