Asymptotics of the norm of elliptical random vectors
In this paper we consider elliptical random vectors in with stochastic representation , where R is a positive random radius independent of the random vector which is uniformly distributed on the unit sphere of and is a given matrix. Denote by ||[dot operator]|| the Euclidean norm in , and let F be the distribution function of R. The main result of this paper is an asymptotic expansion of the probability for F in the Gumbel or the Weibull max-domain of attraction. In the special case that is a mean zero Gaussian random vector our result coincides with the one derived in Hüsler et al. (2002) [1].
Year of publication: |
2010
|
---|---|
Authors: | Hashorva, Enkelejd |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 101.2010, 4, p. 926-935
|
Publisher: |
Elsevier |
Keywords: | Elliptical distribution Gaussian distribution Kotz Type distribution Gumbel max-domain of attraction Tail approximation Density convergence Weak convergence |
Saved in:
Saved in favorites
Similar items by person
-
Random shifting and scaling of insurance risks
Hashorva, Enkelejd, (2014)
-
Tail asymptotic results for elliptical distributions
Hashorva, Enkelejd, (2008)
-
On the asymptotic distribution of certain bivariate reinsurance treaties
Hashorva, Enkelejd, (2007)
- More ...