A gamma tail statistic and its asymptotics
Abstract
Asmussen and Lehtomaa [Distinguishing log-concavity from heavy tails. Risks 5(10), 2017] introduced an interesting function $g$ which is able to distinguish between log-convex and log-concave tail behaviour of distributions, and proposed a randomized estimator for $g$. In this paper, we show that $g$ can also be seen as a tool to detect gamma distributions or distributions with gamma tail. We construct a more efficient estimator $\hat{g}_n$ based on $U$-statistics, propose several estimators of the (asymptotic) variance of $\hat{g}_n$, and study their performance by simulations. Finally, the methods are applied to several data sets of daily precipitation.
- Publication:
-
arXiv e-prints
- Pub Date:
- June 2023
- DOI:
- arXiv:
- arXiv:2306.07577
- Bibcode:
- 2023arXiv230607577I
- Keywords:
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- Statistics - Methodology;
- 62G32;
- 62G05;
- 62G20