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

Viewed

Total article views: 2,373 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,230 990 153 2,373 832 155 166
  • HTML: 1,230
  • PDF: 990
  • XML: 153
  • Total: 2,373
  • Supplement: 832
  • BibTeX: 155
  • EndNote: 166
Views and downloads (calculated since 20 Jun 2017)
Cumulative views and downloads (calculated since 20 Jun 2017)

Viewed (geographical distribution)

Total article views: 2,373 (including HTML, PDF, and XML) Thereof 2,235 with geography defined and 138 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 29 Jun 2024
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.