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

11 September 2022
F. Tang
D. Han
ArXiv (abs)PDFHTML
Abstract

This article proposes a new method of truncated estimation to estimate the tail index α\alphaα of the extremely heavy-tailed distribution with infinite mean or variance. We not only present two truncated estimators α^\hat{\alpha}α^ and α^′\hat{\alpha}^{\prime}α^′ for estimating α\alphaα (0<α≤10<\alpha \leq 10<α≤1) and α\alphaα (1<α≤21<\alpha \leq 21<α≤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.

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