کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5118997 | 1378193 | 2017 | 35 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures
ترجمه فارسی عنوان
استقلال وابستگی و وابستگی در افراطهای فضایی را با استفاده از مخلوط مقیاس گاوس مقایسه کنید
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کلمات کلیدی
وابستگی وابستگی و استقلال، استنتاج احتمالی سانسور شده، کپی فضایی، رویداد فوق العاده، مدل مقیاس تصادفی بیش از حد آستانه،
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
علوم زمین و سیاره ای (عمومی)
چکیده انگلیسی
Gaussian scale mixtures are constructed as Gaussian processes with a random variance. They have non-Gaussian marginals and can exhibit asymptotic dependence unlike Gaussian processes, which are asymptotically independent except in the case of perfect dependence. In this paper, we study the extremal dependence properties of Gaussian scale mixtures and we unify and extend general results on their joint tail decay rates in both asymptotic dependence and independence cases. Motivated by the analysis of spatial extremes, we propose flexible yet parsimonious parametric copula models that smoothly interpolate from asymptotic dependence to independence and include the Gaussian dependence as a special case. We show how these new models can be fitted to high threshold exceedances using a censored likelihood approach, and we demonstrate that they provide valuable information about tail characteristics. In particular, by borrowing strength across locations, our parametric model-based approach can also be used to provide evidence for or against either asymptotic dependence class, hence complementing information given at an exploratory stage by the widely used nonparametric or parametric estimates of the Ï and ÏÌ coefficients. We demonstrate the capacity of our methodology by adequately capturing the extremal properties of wind speed data collected in the Pacific Northwest, US.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Spatial Statistics - Volume 21, Part A, August 2017, Pages 166-186
Journal: Spatial Statistics - Volume 21, Part A, August 2017, Pages 166-186
نویسندگان
Raphaël Huser, Thomas Opitz, Emeric Thibaud,