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Uniform approximation to distributions of extreme order statistics

Published online by Cambridge University Press:  01 July 2016

R.-D. Reiss*
Affiliation:
University of Siegen
*
Postal address: Department of Mathematics, University of Siegen, Hölderlinstr. 3, 59 Siegen 21, West Germany.

Abstract

This paper deals with asymptotic expansions of the distribution of the kth-largest order statistic Zn–k+1:n for the sample size n. These expansions establish higher-order approximations which hold uniformly over all Borel sets. In the particular case of the distribution of Zn–k+1:n under the uniform distribution and the exponential distribution, the approximating measures are linear combinations of ‘negative’ gamma distributions and linear combinations of extreme-value distributions. These results can be extended to the case of the joint distribution of the k largest order statistics. A numerical comparison to a different asymptotic expansion is given where the normal distribution is the leading term.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 1981 

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References

David, H. A. (1970) Order Statistics. Wiley, New York.Google Scholar
Dronskers, J. J. (1958) Approximate formulae for the statistical distributions of extreme values. Biometrika 45, 447470.CrossRefGoogle Scholar
Galambos, J. (1978a) The Asymptotic Theory of Extreme Order Statistics. Wiley, New York.Google Scholar
Galambos, J. (1978b) Extreme value theory in applied probability (abstract). Adv. Appl. Prob. 11, 289.CrossRefGoogle Scholar
Haldane, J. B. S. and Jayakar, S. D. (1963) The distribution of extremal and nearly extremal values in samples from a normal distribution. Biometrika 50, 8994.Google Scholar
Hall, P. (1979) On the rate of convergence of normal extremes. J. Appl. Prob. 16, 433439.CrossRefGoogle Scholar
Hall, W. J. and Wellner, J. A. (1979) The rate of convergence in law of the maximum of exponential sample. Statistica Neerlandica 33, 151154.CrossRefGoogle Scholar
Ikeda, S. and Matsunawa, T. (1976) Uniform asymptotic distribution of extremes. In Essays in Probability and Statistics, ed. Ikeda, et al., Shinko Tsusho, Tokyo, 419432.Google Scholar
Reiss, R.-D. (1975) The asymptotic normality and asymptotic expansions for the joint distribution of several order statistics. In: Limit Theorems of Probability Theory, ed Révész, P. (Keszethey, 1974) North-Holland, Amsterdam.Google Scholar
Reiss, R.-D. (1976) Asymptotic expansions for sample quantiles. Ann. Prob. 4, 249258.CrossRefGoogle Scholar
Reiss, R.-D. (1977) Asymptotic theory for order statistics. Lecture notes, University of Freiburg.Google Scholar
Uzgören, N. T. (1954) The asymptotic development of the distribution of the extreme values of a sample. In Studies in Mathematics and Mechanics. Presented to Richard von Mises. New York.Google Scholar
Weiss, L. (1971) Asymptotic inference about a density function at an end of its range. Naval Res. Logist. Quart. 18, 111114.CrossRefGoogle Scholar