Statistics of Extremes

被引:125
作者
Davison, A. C. [1 ]
Huser, R. [2 ]
机构
[1] Ecole Polytech Fed Lausanne, CH-1015 Lausanne, Switzerland
[2] King Abdullah Univ Sci & Technol, Thuwal 239956900, Saudi Arabia
来源
ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 2 | 2015年 / 2卷
基金
瑞士国家科学基金会;
关键词
asymptotic dependence; asymptotic independence; extrapolation; generalized extreme value distribution; generalized Pareto distribution; max-stability; Pareto process; peaks over thresholds; Poisson process; LIKELIHOOD ESTIMATION; REGULAR VARIATION; RANDOM VECTORS; POINT PROCESS; INFERENCE; MODELS; TAIL; THRESHOLD; INDEPENDENCE; PROBABILITY;
D O I
10.1146/annurev-statistics-010814-020133
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Statistics of extremes concerns inference for rare events. Often the events have never yet been observed, and their probabilities must therefore be estimated by extrapolation of tail models fitted to available data. Because data concerning the event of interestmay be very limited, efficient methods of inference play an important role. This article reviews this domain, emphasizing current research topics. We first sketch the classical theory of extremes for maxima and threshold exceedances of stationary series. We then review multivariate theory, distinguishing asymptotic independence and dependence models, followed by a description of models for spatial and spatiotemporal extreme events. Finally, we discuss inference and describe two applications. Animations illustrate some of the main ideas.
引用
收藏
页码:203 / 235
页数:33
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