Publication detail

Extreme value estimation for correlated observations

HOLEŠOVSKÝ, J. FUSEK, M. MICHÁLEK, J.

Original Title

Extreme value estimation for correlated observations

English Title

Extreme value estimation for correlated observations

Type

conference paper

Language

en

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.

English 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

RIV year

2014

Released

25.06.2014

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

Pages from

359

Pages to

364

Pages count

6

Documents

BibTex


@inproceedings{BUT108396,
  author="Jan {Holešovský} and Michal {Fusek} and Jaroslav {Michálek}",
  title="Extreme value estimation for correlated observations",
  annote="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.",
  address="Brno University of Technology, Faculty of Mechanical Engineering, Institute of Automation and Computer Science",
  booktitle="Mendel 2014 20th International Conference of Soft Computing",
  chapter="108396",
  howpublished="print",
  institution="Brno University of Technology, Faculty of Mechanical Engineering, Institute of Automation and Computer Science",
  year="2014",
  month="june",
  pages="359--364",
  publisher="Brno University of Technology, Faculty of Mechanical Engineering, Institute of Automation and Computer Science",
  type="conference paper"
}