Extremes in multivariate stationary normal sequences

• Autorzy: Mateusz Wiśniewski
• Języki publikacji: EN

Abstrakty

EN

This paper deals with a weak convergence of maximum vectors built on the base of stationary and normal sequences of relatively strongly dependent random vectors. The discussion concentrates on the normality of limits and extends some results of McCormick and Mittal [4] to the multivariate case.

Słowa kluczowe

EN

stationary normal sequences; extreme order statistics

• Wydawca: Institute of Mathematics Polish Academy of Sciences
• Czasopismo: Applicationes Mathematicae
• Rocznik: 1998-1999
• Tom: 25
• Numer: 3
• Strony: 375-379

Daty

wydano

1998

otrzymano

1997-10-05

Twórcy

autor

Mateusz Wiśniewski

• Technical University of Kielce, Al. 1000-Lecia Państwa Polskiego 7, 25-314 Kielce, Poland

Bibliografia

• [1] S. M. Berman, Limit theorems for the maximum term in stationary sequences, Ann. Math. Statist. 35 (1964), 502-516.
• [2] J. Galambos, The Asymptotic Theory of Extreme Order Statistics, Wiley, New York, 1978.
• [3] M. R. Leadbetter, G. Lindgren and H. Rootzén, Extremes and Related Properties of Random Sequences and Processes, Springer, New York, 1983.
• [4] W. P. McCormick and Y. Mittal, On weak convergence of the maximum, Techn. Report No 81, Dept. of Statist. Stanford Univ., 1976.
• [5] Y. Mittal and D. Ylvisaker, Limit distributions for the maxima of stationary Gaussian processes, Stochastic Process. Appl. 3 (1975), 1-18.
• [6] M. Wiśniewski, Extreme order statistics in an equally correlated Gaussian array, Appl. Math. (Warsaw) 22 (1994), 193-200.