Comparison of trend detection methods in GEV models

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F20%3APU137328" target="_blank" >RIV/00216305:26210/20:PU137328 - isvavai.cz</a>
Result on the web
<a href="https://www.tandfonline.com/doi/full/10.1080/03610918.2020.1804580?scroll=top&needAccess=true" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/03610918.2020.1804580?scroll=top&needAccess=true</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/03610918.2020.1804580" target="_blank" >10.1080/03610918.2020.1804580</a>

Result language
angličtina
Original language name
Comparison of trend detection methods in GEV models
Original language description
In recent environmental studies, the examination of extreme events has great impact. The block maxima of environment-related indices can be analyzed by the tools of extreme value theory. For instance, the monthly maxima of the fire weather index at stations in British Columbia might be modeled by GEV distribution, but it is questionable whether the underlying stochastic process is stationary. This property can lead us to different approaches to determine whether there is a significant trend in the past few years’ data or not. One such approach is a likelihood ratio based procedure, which has favorable asymptotic properties, but for realistic sample sizes it might have large decision errors. In this paper, we analyze the properties of the likelihood ratio test for extremes by bootstrap simulations and present a simulation-based procedure to overcome the problem of small sample sizes. We also propose a return level calculation method. Using our theoretical results we reassess the trends of fire weather index monthly maxima in selected stations of British Columbia.
Czech name
—
Czech description
—

Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical
Communications in Statistics Part B: Simulation and Computation
ISSN
0361-0918
e-ISSN
1532-4141
Volume of the periodical
-
Issue of the periodical within the volume
-
Country of publishing house
US - UNITED STATES
Number of pages
16
Pages from-to
1-16
UT code for WoS article
000572788600001
EID of the result in the Scopus database
2-s2.0-85091216178

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