The Annals of Applied Probability

Extreme value theory for a class of nonstationary time series with applications

Xu-Feng Niu

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Abstract

Consider a class of nonstationary time series with the form $Y_t = \mu_t + \xi_t$ where ${\xi_t}$ is a sequence of infinite moving averages of independent random variables with regularly varying tail probabilities and different scale parameters. In this article, the extreme value theory of ${Y_t}$ is studied. Under mild conditions, convergence results for a point process based on the moving averages are proved, and extremal properties of the nonstationary time series, including the convergence of maxima to extremal processes and the limit point process of exceedances, are derived. The results are applied to the analysis of tropospheric ozone data in the Chicago area. Probabilities of monthly maximum ozone concentrations exceeding some specific levels are estimated, and the mean rate of exceedances of daily maximum ozone over the national standard 120 ppb is also assessed.

Article information

Source
Ann. Appl. Probab., Volume 7, Number 2 (1997), 508-522.

Dates
First available in Project Euclid: 14 October 2002

Permanent link to this document
https://projecteuclid.org/euclid.aoap/1034625342

Digital Object Identifier
doi:10.1214/aoap/1034625342

Mathematical Reviews number (MathSciNet)
MR1442324

Zentralblatt MATH identifier
0884.60045

Subjects
Primary: 60G70: Extreme value theory; extremal processes 60G55: Point processes
Secondary: 62M10: Time series, auto-correlation, regression, etc. [See also 91B84]

Keywords
Extreme value distributions Poisson random measure tropospheric ozone analysis threshold exceedances

Citation

Niu, Xu-Feng. Extreme value theory for a class of nonstationary time series with applications. Ann. Appl. Probab. 7 (1997), no. 2, 508--522. doi:10.1214/aoap/1034625342. https://projecteuclid.org/euclid.aoap/1034625342


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