tail event
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2021 ◽  
pp. 102424
Author(s):  
Wen Jiang ◽  
Qiuhua Xu ◽  
Ruige Zhang
Keyword(s):  




2021 ◽  
pp. 102070
Author(s):  
Toan Luu Duc Huynh ◽  
Matteo Foglia ◽  
John A. Doukas
Keyword(s):  


2020 ◽  
pp. 1-12
Author(s):  
Andrija Mihoci ◽  
Wolfgang Karl Härdle ◽  
Cathy Yi-Hsuan Chen
Keyword(s):  


2019 ◽  
Vol 93 (3-4) ◽  
pp. 333-349 ◽  
Author(s):  
Remco van der Hofstad ◽  
Harsha Honnappa

Abstract We establish sharp tail asymptotics for componentwise extreme values of bivariate Gaussian random vectors with arbitrary correlation between the components. We consider two scaling regimes for the tail event in which we demonstrate the existence of a restricted large deviations principle and identify the unique rate function associated with these asymptotics. Our results identify when the maxima of both coordinates are typically attained by two different versus the same index, and how this depends on the correlation between the coordinates of the bivariate Gaussian random vectors. Our results complement a growing body of work on the extremes of Gaussian processes. The results are also relevant for steady-state performance and simulation analysis of networks of infinite server queues.



2019 ◽  
Vol 208 (1) ◽  
pp. 282-298 ◽  
Author(s):  
Cathy Yi-Hsuan Chen ◽  
Wolfgang Karl Härdle ◽  
Yarema Okhrin
Keyword(s):  


2017 ◽  
Vol 19 (1) ◽  
pp. 49-63 ◽  
Author(s):  
Wolfgang Karl Härdle ◽  
David Kuo Chuen Lee ◽  
Sergey Nasekin ◽  
Alla Petukhina


2017 ◽  
Author(s):  
Cathy Yi-Hsuan Chen ◽  
Wolfgang K. HHrdle ◽  
Yarema Okhrin
Keyword(s):  


2017 ◽  
Author(s):  
Sergey Nasekin ◽  
Wolfgang K. Härdle ◽  
David Kuo Chuen Lee


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