Self-normalized partial sums of heavy-tailed time series

被引:0
作者
Matsui, Muneya [1 ]
Mikosch, Thomas [2 ]
Wintenberger, Olivier [3 ,4 ]
机构
[1] Nanzan Univ, Dept Business Adm, 18 Yamazato cho,Showa ku, Nagoya, Aichi 4668673, Japan
[2] Univ Copenhagen, Dept Math, Univ Pk 5, DK-2100 Copenhagen, Denmark
[3] UPMC Univ Paris 06, Sorbonne Univ, Lab Probabil Stat & Modelisat, F-75005 Paris, France
[4] Univ Vienna, Inst CNRS Pauli, Vienna, Austria
关键词
Regularly varying sequence; Extremal clusters; Sums; Maxima; Self-normalization; Ratio limits; CONVERGENCE; MAXIMA;
D O I
10.1016/j.spa.2025.104729
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We study the joint limit behavior of sums, maxima and l(p)-type moduli for samples taken from an R-d-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.
引用
收藏
页数:25
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