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HOLEŠOVSKÝ, J. FUSEK, M. MICHÁLEK, J.
Original Title
Extreme value estimation for correlated observations
Type
conference paper
Language
English
Original Abstract
Statistical modeling of extreme events is the object of interest in many application areas. When estimating such rare events from a time series, extreme value theory is commonly used. In that case, series with independent members are required. However, the assumption of independence is not satisfied in many situations. There are two approaches (block maxima, peaks-over-threshold) which result in series with independent members, but the length of the series is substantially reduced. In this paper, stationary series with short-time dependence described by the extremal index theta is considered, and two estimators of theta are introduced. Behavior of the estimators is assessed using simulations. The described methods are used in an analysis of real hydrological data, and compared with classical peaks-over-threshold approach.
Keywords
extreme value distribution, extremal index, peaks over threshold, stationary process
Authors
HOLEŠOVSKÝ, J.; FUSEK, M.; MICHÁLEK, J.
RIV year
2014
Released
25. 6. 2014
Publisher
Brno University of Technology, Faculty of Mechanical Engineering, Institute of Automation and Computer Science
Location
Brno, Czech Republic
ISBN
978-80-214-4984-8
Book
Mendel 2014 20th International Conference of Soft Computing
1803-3814
Periodical
Mendel Journal series
State
Czech Republic
Pages from
359
Pages to
364
Pages count
6
BibTex
@inproceedings{BUT108396, author="Jan {Holešovský} and Michal {Fusek} and Jaroslav {Michálek}", title="Extreme value estimation for correlated observations", booktitle="Mendel 2014 20th International Conference of Soft Computing", year="2014", journal="Mendel Journal series", pages="359--364", publisher="Brno University of Technology, Faculty of Mechanical Engineering, Institute of Automation and Computer Science", address="Brno, Czech Republic", isbn="978-80-214-4984-8", issn="1803-3814" }