@article{EJP935,
author = {Arijit Chakrabarty},
title = {Asymptotic Normality of Hill Estimator for Truncated Data},
journal = {Electron. J. Probab.},
fjournal = {Electronic Journal of Probability},
volume = {16},
year = {2011},
keywords = {heavy tails, truncation, second order regular variation, Hill estimator, asymptotic normality},
abstract = {The problem of estimating the tail index from truncated data is addressed in [2]. In that paper, a sample based (and hence random) choice of k is suggested, and it is shown that the choice leads to a consistent estimator of the inverse of the tail index. In this paper, the second order behavior of the Hill estimator with that choice of k is studied, under some additional assumptions. In the untruncated situation, asymptotic normality of the Hill estimator is well known for distributions whose tail belongs to the Hall class, see [11]. Motivated by this, we show the same in the truncated case for that class.},
pages = {no. 74, 2039-2058},
issn = {1083-6489},
doi = {10.1214/EJP.v16-935},
url = {http://ejp.ejpecp.org/article/view/935}}