Asymptotic expansion of Gaussian chaos via probabilistic approach

Hashorva, Enkelejd and Korshunov, Dmitry and Piterbarg, Vladimir I. (2015) Asymptotic expansion of Gaussian chaos via probabilistic approach. Extremes, 18 (3). pp. 315-347. ISSN 1386-1999

Full text not available from this repository.


For a centered d-dimensional Gaussian random vector ξ = (ξ 1, … , ξ d ) and a homogeneous function h : ℝ d → ℝ we derive asymptotic expansions for the tail of the Gaussian chaos h(ξ) given the function h is sufficiently smooth. Three challenging instances of the Gaussian chaos are the determinant of a Gaussian matrix, the Gaussian orthogonal ensemble and the diameter of random Gaussian clouds. Using a direct probabilistic asymptotic method, we investigate both the asymptotic behaviour of the tail distribution of h(ξ) and its density at infinity and then discuss possible extensions for some general ξ with polar representation.

Item Type: Journal Article
Journal or Publication Title: Extremes
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/2600/2613
Departments: Faculty of Science and Technology > Mathematics and Statistics
ID Code: 74012
Deposited By: ep_importer_pure
Deposited On: 18 Jun 2015 05:58
Refereed?: Yes
Published?: Published
Last Modified: 11 Feb 2020 08:33

Actions (login required)

View Item View Item