Skip to main content
Log in

On an improvement of Hill and some other estimators

  • Published:
Lithuanian Mathematical Journal Aims and scope Submit manuscript

Abstract

In the paper, we propose a new idea in the tail-index estimation. This idea allows us to improve the asymptotic performance of the classical Hill estimator and other most popular estimators over the range of the parameters present in the second-order regular-variation condition. We prove the asymptotic normality of the introduced estimators and provide a comparison (using the asymptotic mean-squared error) with other estimators of the tail index.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. S. Csorgő and D. Mason, Central limit theorem for sums of extreme values, Math. Proc. Cambridge Philos. Soc., 98:547–558, 1985.

    Article  MathSciNet  Google Scholar 

  2. J. Danielsson, D.W. Jansen, and C.G. de Vries, The method of moments ratio estimator for the tail shape parameter, Commun. Stat., Theory Methods, 25:711–720, 1986.

    Article  Google Scholar 

  3. R. Davis and S. Resnick, Tail estimates motivated by extreme value theory, Ann. Stat., 12:1467–1487, 1984.

    Article  MathSciNet  MATH  Google Scholar 

  4. L. de Haan and A. Ferreira, Extreme Value Theory: An Introduction, Springer, New York, 2006.

    Google Scholar 

  5. L. de Haan and L. Peng, Comparison of tail-index estimators, Stat. Neerl., 52:60–70, 1998.

    Article  MATH  Google Scholar 

  6. L. de Haan and S. Resnick, On asymptotic normality of the Hill estimator, Stoch. Models, 14:849–867, 1998.

    Article  MATH  Google Scholar 

  7. A.L.M. Dekkers, J.H.J. Einmahl, and L. de Haan, A moment estimator for the index of an extreme-value distribution, Ann. Stat., 17:1833–1855, 1989.

    Article  MATH  Google Scholar 

  8. H. Drees, On smooth statistical tail functionals, Scand. J. Stat., 25:187–210, 1998.

    Article  MathSciNet  MATH  Google Scholar 

  9. M.I. Fraga Alves, M.I. Gomes, L. de Haan, and C. Neves, Mixed moment estimator and location invariant alternatives, Extremes, 12:149–185, 2009.

    Article  MathSciNet  MATH  Google Scholar 

  10. C. Goldie and R. Smith, Slow variation with remainder: Theory and applications, Q. J. Math., 38:45–71, 1987.

    Article  MathSciNet  MATH  Google Scholar 

  11. M.I. Gomes, L. Canto e Castro, M.I. Fraga Alves, and D. Pestana, Statistics of extremes for IID data and breakthroughs in the estimation of the extreme value index: Laurens de Haan leading contributions, Extremes, 11:3–34, 2008.

    Article  MathSciNet  MATH  Google Scholar 

  12. M.I. Gomes and C. Neves, Asymptotic comparison of the mixed moment and classical extreme value index estimators, Stat. Probab. Lett., 78:643–653, 2008.

    Article  MathSciNet  MATH  Google Scholar 

  13. E. Hausler and J. Teugels, On asymptotic normality of Hill’s estimator for the exponent of regular variation, Statistics, 13:743–756, 1985.

    Article  Google Scholar 

  14. B.M. Hill, A simple general approach to inference about the tail of a distribution, Ann. Stat., 3(5):1163–1174, 1975.

    Article  MATH  Google Scholar 

  15. J. Li, Z. Peng, and S. Nadarajah, A class of unbiased location invariant Hill-type estimators for heavy-tailed distributions, Electron. J. Stat., 2:829–847, 2008.

    Article  MathSciNet  Google Scholar 

  16. D.M. Mason, Law of large numbers for sums of extreme values, Ann. Probab., 10:754–764, 1982.

    Article  MathSciNet  MATH  Google Scholar 

  17. M.M. Meerschaert and H.-P. Scheffer, A simple robust estimation method for the thickness of heavy tail, J. Stat. Plann. Infer., 71:19–34, 1998.

    Article  MATH  Google Scholar 

  18. O.A. Oliveira, M.I. Gomes, and M.I. Fraga Alves, Improvements in the estimation of a heavy tail, REVSTAT, 4:81–109, 2006.

    MathSciNet  MATH  Google Scholar 

  19. V. Paulauskas, A new estimator for a tail index, Acta Appl. Math., 79:55–67, 2003.

    Article  MathSciNet  MATH  Google Scholar 

  20. V. Paulauskas and M. Vaičiulis, Several modifications of DPR estimator of the tail index, Lith. Math. J., 51:36–50, 2011.

    Article  MathSciNet  Google Scholar 

  21. J. Pickands, Statistical inference using extreme order statistics, Ann. Stat., 3:119–131, 1975.

    Article  MathSciNet  MATH  Google Scholar 

  22. D. Politis, A new approach on estimation of the tail index, C. R. Math., Acad. Sci. Paris, 335:279–282, 2002.

    Article  MathSciNet  MATH  Google Scholar 

  23. A. Renyi, On the theory of order statistics, Acta Math. Acad. Sci. Hung., 4:191–231, 1953.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vygantas Paulauskas.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Paulauskas, V., Vaičiulis, M. On an improvement of Hill and some other estimators. Lith Math J 53, 336–355 (2013). https://doi.org/10.1007/s10986-013-9212-x

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10986-013-9212-x

MSC

Keywords

Navigation