Asymptotic distribution for the sum and maximum of Gaussian processes

Journal of Applied Probability

Volumn 37, Issue 4, 2000, Pages 958-971

  McCormick, W P ^a   Qi, Y ^a  

^a UNIVERSITY OF GEORGIA   (United States)

Author keywords

Gaussian process; Maximum; Strongly dependent; Sum; Weakly dependent

Indexed keywords

EID: 85037761590     PISSN: 00219002     EISSN: None     Source Type: Journal    
DOI: 10.1017/S0021900200018155     Document Type: Article

References (7)

1. CHOW, T. L. AND TEUGELS, J. L. (1978). The sum and the maximum of i.i.d. random variables. In Proceedings of the Second Prague Symposium on Asymptotic Statistics, eds P. Mandl and M. Huškova. North Holland, Amsterdam, pp. 81-92.
2. HO, H. C. AND HSING, T. (1996). On the asymptotic joint distribution of the sum and maximum of stationary normal random variables. J. Appl. Prob. 33, 138-145.
3. HO, H. C. AND MCCORMICK, W. P. (1999). Asymptotic distribution of sum and maximum for strongly dependent Gaussian processes. J. Appl. Prob. 36, 1031-1044.
4. HSING, T. (1995). A note on the asymptotic independence of the sum and maximum of strongly mixing stationary random variables. Ann. Prob. 23, 938-947.
5. LEADBETTER, M. R., LINDGREN, G. AND ROOTZEN, H. (1983). Extremes and Related Properties of Stationary Sequences and Processes. Springer, New York.
6. MCCORMICK, W. P. (1980). Weak convergence for the maxima of stationary Gaussian processes using random normalization. Ann. Prob. 8, 483-497.
7. MCCORMICK, W. P. AND MITTAL, Y. (1976). On weak convergence of the maximum. Tech. Rept 81, Dept of Statistics. Stanford University.