关于强依赖情况下的高斯三角形阵列

IF 1.1 3区数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Extremes Pub Date : 2024-09-03 DOI:10.1007/s10687-024-00491-3

Evgeniy Savinov

引用次数: 0

摘要

我们研究了强依赖条件下高斯三角形阵列中极值的行为。通过扩展以前的结果，我们确定了收敛到高斯分布和 Gumbel 分布混合物的条件，而不要求静态性。我们的研究结果为这些模型的应用，尤其是分析空气中的臭氧浓度提供了启示。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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On Gaussian triangular arrays in the case of strong dependence

We investigate the behavior of extreme values in Gaussian triangular arrays under strong dependence conditions. By extending previous results, we establish conditions for convergence to a mixture of Gaussian and Gumbel distributions without requiring stationarity. Our findings offer insights into the application of these models, particularly for analyzing air ozone concentrations.

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来源期刊

Extremes MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY

CiteScore

2.20

自引率

7.70%

发文量

审稿时长

>12 weeks

期刊介绍： Extremes publishes original research on all aspects of statistical extreme value theory and its applications in science, engineering, economics and other fields. Authoritative and timely reviews of theoretical advances and of extreme value methods and problems in important applied areas, including detailed case studies, are welcome and will be a regular feature. All papers are refereed. Publication will be swift: in particular electronic submission and correspondence is encouraged. Statistical extreme value methods encompass a very wide range of problems: Extreme waves, rainfall, and floods are of basic importance in oceanography and hydrology, as are high windspeeds and extreme temperatures in meteorology and catastrophic claims in insurance. The waveforms and extremes of random loads determine lifelengths in structural safety, corrosion and metal fatigue.