Self-normalized partial sums of heavy-tailed time series

IF 1.1 2区 数学 Q3 STATISTICS & PROBABILITY
Muneya Matsui , Thomas Mikosch , Olivier Wintenberger
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引用次数: 0

Abstract

We study the joint limit behavior of sums, maxima and p-type moduli for samples taken from an Rd-valued regularly varying stationary sequence with infinite variance. As a consequence, we can determine the distributional limits for ratios of sums and maxima, studentized sums, and other self-normalized quantities in terms of hybrid characteristic-distribution functions and Laplace transforms. These transforms enable one to calculate moments of the limits and to characterize the differences between the iid and stationary cases in terms of indices which describe effects of extremal clustering on functionals acting on the dependent sequence.
重尾时间序列的自标准化部分和
研究了具有无穷方差的rd值正则变平稳序列样本的和、极大值和p型模的联合极限行为。因此,我们可以根据混合特征分布函数和拉普拉斯变换确定和与最大值之比、学生化和和其他自归一化量的分布极限。这些变换使人们能够计算极限的矩,并根据描述极值聚类对作用于相关序列的泛函的影响的指标来表征iid和平稳情况之间的差异。
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来源期刊
Stochastic Processes and their Applications
Stochastic Processes and their Applications 数学-统计学与概率论
CiteScore
2.90
自引率
7.10%
发文量
180
审稿时长
23.6 weeks
期刊介绍: Stochastic Processes and their Applications publishes papers on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests. Characterization, structural properties, inference and control of stochastic processes are covered. The journal is exacting and scholarly in its standards. Every effort is made to promote innovation, vitality, and communication between disciplines. All papers are refereed.
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