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On the asymptotic joint distribution of the sum and maximum of stationary normal random variables

Part of: Stochastic processes Limit theorems

Published online by Cambridge University Press:  14 July 2016

Hwai-Chung Ho  and
Tailen Hsing
Hwai-Chung Ho*
Affiliation:
Academia Sinica
Tailen Hsing*
Affiliation:
Texas A&M University
*
∗ Postal address: Institute of Statistical Science, Academia Sinica, Taipei, Taiwan, Republic of China.
∗∗ Postal address: Department of Statistics, Texas A&M University, College Station, Texas 77843–3143, USA.
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Abstract

Let X 1, X 2, ·· ·be stationary normal random variables with ρn = cov(X 0, Xn ). The asymptotic joint distribution of and is derived under the condition ρn log n → γ [0,∞). It is seen that the two statistics are asymptotically independent only if γ = 0.

Keywords

GAUSSIAN PROCESSEXTREME VALUEPARTIAL SUMLONG-RANGE DEPENDENCE

MSC classification

Primary: 60G70: Extreme value theory; extremal processes
Secondary: 60F05: Central limit and other weak theorems 60G15: Gaussian processes

Information

Type
Research Papers
Information
Journal of Applied Probability , Volume 33 , Issue 1 , March 1996 , pp. 138 - 145
Copyright
Copyright © Applied Probability Trust 1996 

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Footnotes

Research of Tailen Hsing supported by NAVY-ONR Grant N00014-92-J-1007.

References

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