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

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

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
Download
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.