On the accuracy of inference on heavy-tailed distributions
Novak, Serguei 
ORCID: https://orcid.org/0000-0001-7929-7641
(2013)
On the accuracy of inference on heavy-tailed distributions.
Theory of Probability and Its Applications, 58
(3)
.
pp. 509-518.
ISSN 0040-585X
[Article]
(doi:10.1137/S0040585X97986710)
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Abstract
This paper suggests a simple method of deriving nonparametric lower bounds of the accuracy of statistical inference on heavy-tailed distributions. We present lower bounds of the mean squared error of the tail index, the tail constant, and extreme quantiles estimators. The results show that the normalizing sequences of robust estimators must depend in a specific way on the tail index and the tail constant.
| Item Type: | Article |
|---|---|
| Additional Information: | Published online: 16 September 2014 |
| Research Areas: | A. > School of Science and Technology > Design Engineering and Mathematics |
| Item ID: | 18124 |
| Notes on copyright: | Published in Theory of Probability & Its Applications in Volume 58, Issue 3, published by the Society of Industrial and Applied Mathematics (SIAM). Copyright © 2014 Society of Industrial and Applied Mathematics. |
| Useful Links: | |
| Depositing User: | Serguei Novak |
| Date Deposited: | 14 Oct 2015 10:00 |
| Last Modified: | 30 Nov 2022 00:21 |
| URI: | https://eprints.mdx.ac.uk/id/eprint/18124 |
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