Censored pairwise likelihood-based tests for mixing coefficient of spatial max-mixture models

Autor: Abu-Awwad, Abdul-Fattah, Maume-Deschamps, Véronique, Pierre, Ribereau

Max-mixture processes are defined as Z = max(aX, (1 -- a)Y) with X an asymptotic dependent (AD) process, Y an asymptotic independent (AI) process and a $\in$ [0, 1]. So that, the mixing coefficient a may reveal the strength of the AD part present in

Externí odkaz: http://arxiv.org/abs/1712.02990

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

Autor: Véronique Maume-Deschamps, Pierre Ribereau, Abdul-Fattah Abu-Awwad

Publikováno v: Statistical Inference for Stochastic Processes. 24:241-276

Max-stable processes have been expanded to quantify extremal dependence in spatiotemporal data. Due to the interaction between space and time, spatiotemporal data are often complex to analyze. So, characterizing these dependencies is one of the cruci

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::51d44060a0d9805de3abb401bbd406e4
https://doi.org/10.1007/s11203-020-09232-2

Spatial Risk Measure for Max-Stable and Max-Mixture Processes

Autor: Véronique Maume-Deschamps, Pierre Ribereau, Manaf Ahmed, Céline Vial

Publikováno v: Stochastics: An International Journal of Probability and Stochastic Processes
Stochastics: An International Journal of Probability and Stochastic Processes, 2020, 92 (7), pp.1005-1020. ⟨10.1080/17442508.2019.1687703⟩
Stochastics: An International Journal of Probability and Stochastic Processes, Taylor & Francis: STM, Behavioural Science and Public Health Titles, In press, 92 (7), pp.1005-1020. ⟨10.1080/17442508.2019.1687703⟩

In this paper, we consider isotropic and stationary max-stable, inverse max-stable and max-mixture processes $X=(X(s))\_{s\in\bR^2}$ and the damage function $\cD\_X^{\nu}= |X|^\nu$ with $0

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe3300d5c842f9ce4b35a87e2c2e4c44
https://hal.science/hal-01546570v2/file/Max-Mixture_version_du_24juin2017.pdf

Improving Probability-Weighted Moment Methods for the Generalized Extreme Value Distribution

Autor: Jean Diebolt, Armelle Guillou, Philippe Naveau, Pierre Ribereau

Publikováno v: Revstat Statistical Journal, Vol 6, Iss 1 (2008)

In 1985 Hosking et al. estimated with the so-called Probability-Weighted Moments (PWM) method the parameters of the Generalized Extreme Value (GEV) distribution, the latter being classically fitted to maxima of sequences of independent and identicall

Externí odkaz: https://doaj.org/article/e9c84211b0724f758c0a3975e814b888

Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection

Autor: Alexis Hannart, Pierre Ribereau, Raphaël Huser, Philippe Naveau

Publikováno v: Water Resources Research. 52:2753-2769

In statistics, extreme events are often defined as excesses above a given large threshold. This definition allows hydrologists and flood planners to apply Extreme-Value Theory (EVT) to their time series of interest. Even in the stationary univariate

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::02af080bda89a758c286cb68a93e826e
https://doi.org/10.1002/2015wr018552