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A new method for estimating the tail index using truncated sample sequence

Statistics Theory 2022-09-13 v1 Applications Statistics Theory

Abstract

This article proposes a new method of truncated estimation to estimate the tail index α\alpha of the extremely heavy-tailed distribution with infinite mean or variance. We not only present two truncated estimators α^\hat{\alpha} and α^\hat{\alpha}^{\prime} for estimating α\alpha (0<α10<\alpha \leq 1) and α\alpha (1<α21<\alpha \leq 2) respectively, but also prove their asymptotic statistical properties. The numerical simulation results comparing the six known estimators in estimating error, the Type I Error and the power of estimator show that the performance of the two new truncated estimators is quite good on the whole.

Keywords

Cite

@article{arxiv.2209.04772,
  title  = {A new method for estimating the tail index using truncated sample sequence},
  author = {F. Q. Tang and D. Han},
  journal= {arXiv preprint arXiv:2209.04772},
  year   = {2022}
}
R2 v1 2026-06-28T01:04:28.860Z