Outlier identification based on local extreme quantile estimation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F16%3APU119354" target="_blank" >RIV/00216305:26110/16:PU119354 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Outlier identification based on local extreme quantile estimation
Original language description
An extensive time series observations serve for an input in wide range of technical, economical and environmental application areas. However, the verification of validity of such data is necessary condition for any further analysis. Correctness of the data can be proven with respect to various criteria, mainly the attention is focused on detecting possible outliers in the series. Among others, these comprise observations corrupted by failure of any measuring instrument or influence of other than the quantity of interest. In this contribution we present an advanced technique for time series outlier detection based on extreme value analysis. Extreme value theory is being successfully applied in many branches, and hence provides an adequate framework for detection of rare events such as outliers. The suitability of the method proposed is also discussed with respect to eventual automation of the whole procedure. The method was applied for validation of hourly air pollution data obtained in Brno, Czech Republic. The measurements were provided by automated instruments at locations with high traffic and industrial load. The proposed method might simplify the procedure of such extensive data verification.
Czech name
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Czech description
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Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of 22nd International Conference on Soft Computing MENDEL 2016
ISBN
978-80-214-5365-4
ISSN
1803-3814
e-ISSN
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Number of pages
6
Pages from-to
255-260
Publisher name
Brno University of Technology
Place of publication
Brno, Czech Republic
Event location
Brno
Event date
Jun 8, 2016
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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