A gamma tail statistic and its asymptotics

Toshiya Iwashita and Bernhard Klar

Statistica Neerlandica, 2024, vol. 78, issue 2, 264-280

Abstract: Asmussen and Lehtomaa [Distinguishing log‐concavity from heavy tails. Risks 5(10), 2017] introduced an interesting function g$$ g $$ which is able to distinguish between log‐convex and log‐concave tail behavior of distributions, and proposed a randomized estimator for g$$ g $$. In this paper, we show that g$$ g $$ can also be seen as a tool to detect gamma distributions or distributions with gamma tail. We construct a more efficient estimator ĝn$$ {\hat{g}}_n $$ based on U$$ U $$‐statistics, propose several estimators of the (asymptotic) variance of ĝn$$ {\hat{g}}_n $$, and study their performance by simulations. Finally, the methods are applied to several datasets of daily precipitation.

Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/stan.12316

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:stanee:v:78:y:2024:i:2:p:264-280

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0039-0402

Access Statistics for this article

Statistica Neerlandica is currently edited by Miroslav Ristic, Marijtje van Duijn and Nan van Geloven

More articles in Statistica Neerlandica from Netherlands Society for Statistics and Operations Research
Bibliographic data for series maintained by Wiley Content Delivery ().