Gaussian approximation of conditional elliptical random vectors

Stochastic Models

Volumn 22, Issue 3, 2006, Pages 441-457

  Hashorva, Enkelejd ^a,b  

^a UNIVERSITY OF BERN   (Switzerland)

^b Allianz Suisse   (Switzerland)

Author keywords

Conditional distribution; Elliptical random vectors; Gaussian approximation; Gumbel max domain of attraction; Weak convergence

Indexed keywords

APPROXIMATION THEORY; MATRIX ALGEBRA; MULTIVARIABLE CONTROL SYSTEMS; NUMBER THEORY; RANDOM PROCESSES; SET THEORY; THEOREM PROVING;

CONDITIONAL DISTRIBUTION; ELLIPTICAL RANDOM VECTORS; GAUSSIAN APPROXIMATION; GUMBEL MAX-DOMAIN OF ATTRACTION; WEAK CONVERGENCE;

VECTORS;

EID: 33747163613     PISSN: 15326349     EISSN: 15324214     Source Type: Journal    
DOI: 10.1080/15326340600820414     Document Type: Article

References (10)

1. Berman, M.S. Sojourns and Extremes of Stochastic Processes; Wadsworth & Brooks: Cole, 1992.
2. Billingsley, P. Weak Convergence of Probability Measures; Wiley: New York, 1968.
3. Cambanis, S.; Huang, S.; Simons, G. On the theory of elliptically contured distributions. J. Multivariate Anal. 1981, 11, 368-385.
4. de Haan, L. On Regular Variation and Its Applications to the Weak Convergence of Sample Extremes; Mathematisch Centrum Amsterdam, 1970.
5. Falk, M.; Hüsler, J.; Reiss, R.-D. Laws of Small Numbers: Extremes and Rare Event; DMV Seminar, 2nd Ed.; Birkhäuser: Basel, 2004; Vol. 23.
6. Fang, K.-T.; Kotz, S.; Ng, K.-W. Symmetric Multivariate and Related Distributions; Chapman & Hall: London, 1990.
7. Hashorva, E. Extremes of asymptotically spherical and elliptical random vectors. Insurance: Mathematics and Economics 2005, 36 (3), 285-302.
8. Kallenberg, O. Foundations of Modern Probability, Springer: New York, 1997.
9. Kotz, S.; Nadarajah, S. Extreme Value Distributions, Theory and Applications; Imperial College Press, 2000.
10. Resnick, S.I. Extreme Values, Regular Variation and Point Processes; Springer: New York, 1987.