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Testing for the expected number of exceedances in strongly dependent seasonal time series

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2021

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Ghosh, Sucharita

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https://doi.org/10.1080/10485252.2021.1977301
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Journal of Nonparametric Statistics. Taylor & Francis. 2021, 33(3-4), pp. 417-434. ISSN 1048-5252. eISSN 1029-0311. Available under: doi: 10.1080/10485252.2021.1977301

Zusammenfassung

We consider seasonal time series models with a strongly dependent residual process. The question of testing for a change in the expected number of exceedances is addressed. Based on a functional limit theorem for seasonal empirical processes, a test of the null hypothesis of no change is proposed. The method is applied to daily temperature series at various locations in Switzerland. The test reveals interesting differences in the effect of global warming on seasonal temperature exceedances.

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510 Mathematik

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ISO 690BERAN, Jan, Britta STEFFENS, Sucharita GHOSH, 2021. Testing for the expected number of exceedances in strongly dependent seasonal time series. In: Journal of Nonparametric Statistics. Taylor & Francis. 2021, 33(3-4), pp. 417-434. ISSN 1048-5252. eISSN 1029-0311. Available under: doi: 10.1080/10485252.2021.1977301
BibTex
@article{Beran2021Testi-55173,
  year={2021},
  doi={10.1080/10485252.2021.1977301},
  title={Testing for the expected number of exceedances in strongly dependent seasonal time series},
  number={3-4},
  volume={33},
  issn={1048-5252},
  journal={Journal of Nonparametric Statistics},
  pages={417--434},
  author={Beran, Jan and Steffens, Britta and Ghosh, Sucharita}
}
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