Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-27T22:01:37.820Z Has data issue: false hasContentIssue false

On the rate of convergence of normal extremes

Published online by Cambridge University Press:  14 July 2016

Peter Hall*
Affiliation:
University of Melbourne
*
Present address: Department of Statistics, S.G.S., The Australian National University, P.O. Box 4, Canberra, A.C.T. 2600, Australia.

Abstract

Let Yn denote the largest of n independent N(0, 1) variables. It is shown that if the constants an and bn are chosen in an optimal way then the rate of convergence of (Ynbn)/an to the extreme value distribution exp(–e–x), as measured by the supremum metric or the Lévy metric, is proportional to 1/log n.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 1979 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abramowtiz, M. and Stegun, I. A. (1964) Handbook of Mathematical Functions. National Bureau of Standards, Washington, D.C.Google Scholar
Cramér, H. (1946) Mathematical Methods of Statistics. Princeton University Press, Princeton, N.J.Google Scholar
David, H. A. (1970) Order Statistics. Wiley, New York.Google Scholar
Fisher, R. A. and Tippett, L. H. C. (1928) Limiting forms of the frequency distribution of the largest or smallest member of a sample. Proc. Camb. Phil. Soc. 24, 180190.CrossRefGoogle Scholar
Gnedenko, B. V. (1943) Sur la distribution limite du terme maximum d'une série aléatoire. Ann. Math. 44, 423453.CrossRefGoogle Scholar
Zolotarev, V. M. (1967) A generalization of the Lindeberg-Feller theorem. Theory Prob. Appl. 12, 608618.CrossRefGoogle Scholar