Articles | Volume 24, issue 4
https://doi.org/10.5194/npg-24-737-2017
https://doi.org/10.5194/npg-24-737-2017
Research article
 | 
06 Dec 2017
Research article |  | 06 Dec 2017

Optimal heavy tail estimation – Part 1: Order selection

Manfred Mudelsee and Miguel A. Bermejo

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Manfred Mudelsee on behalf of the Authors (24 Oct 2017)  Author's response   Manuscript 
ED: Reconsider after major revisions (further review by editor and referees) (02 Nov 2017) by Jinqiao Duan
ED: Referee Nomination & Report Request started (03 Nov 2017) by Jinqiao Duan
RR by Anonymous Referee #1 (03 Nov 2017)
ED: Publish as is (06 Nov 2017) by Jinqiao Duan
AR by Manfred Mudelsee on behalf of the Authors (06 Nov 2017)
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Short summary
Risk analysis of extremes has high socioeconomic relevance. Of crucial interest is the tail probability, P, of the distribution of a variable, which is the chance of observing a value equal to or greater than a certain threshold value, x. Many variables in geophysical systems (e.g. climate) show heavy tail behaviour, where P may be rather large. In particular, P decreases with x as a power law that is described by a parameter, α. We present an improved method to estimate α on data.