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Rates of uniform convergence of extreme order statistics

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Summary

Bounds for the convergence uniformly over all Borel sets of the largest order statistic as well as of the joint distribution of extremes are established which reveal in which way these rates are determined by the distance of the underlying density from the density of the corresponding generalized Pareto distribution.

The results are highlighted by several examples among which there is a bound for the rate at which the joint distribution of thek largest order statistics from a normal distribution converges uniformly to its limit.

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References

  1. Cohen, J. P. (1982). Convergence rates for the ultimate and penultimate approximation in extreme-value theory,Adv. Appl. Prob.,14, 833–854.

    Article  MathSciNet  Google Scholar 

  2. Cramér, H. (1946).Mathematical Methods of Statistics, Princeton University Press, Princeton N.J.

    MATH  Google Scholar 

  3. Falk, M. (1984).Uniform Convergence of Extreme Order Statistics I, Preprint 122, University of Siegen.

  4. Galambos, J. (1978).The Asymptotic Theory of Extreme Order Statistics, Wiley, New York.

    MATH  Google Scholar 

  5. Gnedenko, B. (1943). Sur la distribution limite du terme maximum d'une série aléatoire,Ann. Math.,44, 423–453.

    Article  MathSciNet  Google Scholar 

  6. Hall, P. (1979). On the rate of convergence of normal extremes,J. Appl. Prob.,16, 433–439.

    Article  MathSciNet  Google Scholar 

  7. Hall, W. J. and Wellner, J. A. (1979). The rate of convergence in law of the maximum of an exponential sample,Statist. Neerlandica,33, 151–154.

    Article  MathSciNet  Google Scholar 

  8. Ikeda, S. (1963). Asymptotic equivalence of probability distributions with applications to some problems of asymptotic independence,Ann. Inst. Statist. Math.,15, 87–116.

    Article  MathSciNet  Google Scholar 

  9. Ikeda, S. (1968). Asymptotic equivalence of real probability distributions,Ann. Inst. Statist. Math.,20, 339–362.

    Article  MathSciNet  Google Scholar 

  10. Ikeda, S. and Matsunawa, T. (1976). Uniform asymptotic distribution of extremes, inEssays in Probability and Statistics (eds. S. Ikeda et al.), Shinko Tsusho, Tokyo, 419–432.

    Google Scholar 

  11. Kohne, W. and Reiss, R.-D. (1983). A note on uniform approximation to distributions of extreme order statistics,Ann. Inst. Statist. Math.,35, 343–345.

    Article  MathSciNet  Google Scholar 

  12. Kraft, C. (1955). Some conditions for consistency and uniform consistency of statistical procedures,University of California Publications in Statistics,2, 125–142.

    MathSciNet  MATH  Google Scholar 

  13. LeCam, L. (1970). On the assumptions used to prove asymptotic normality of the maximum likelihood estimates,Ann. Math. Statist.,41, 802–828.

    Article  MathSciNet  Google Scholar 

  14. Pfanzagl, J. (1982).Contributions to a General Asymptotic Statistical Theory, Springer, Berlin.

    Book  Google Scholar 

  15. Pickands, J. III (1975). Statistical inference using extreme order statistics,Ann. Statist.,3, 119–131.

    Article  MathSciNet  Google Scholar 

  16. Reiss, R.-D. (1974). On the accuracy of the normal approximation for quantiles,Ann. Prob.,2, 741–744.

    Article  MathSciNet  Google Scholar 

  17. Reiss, R.-D. (1976). Asymptotic expansions for sample quantiles,Ann. Prob.,4, 249–258.

    Article  MathSciNet  Google Scholar 

  18. Reiss, R.-D. (1977). Asymptotic theory for order statistics,Lecture notes, University of Freiburg.

  19. Reiss, R.-D. (1981). Uniform approximation to distributions of extreme order statistics,Adv. Appl. Prob.,13, 533–547.

    Article  MathSciNet  Google Scholar 

  20. Reiss, R.-D. (1984).Statistical Inference Using Approximate Extreme Value Models, Preprint 124, University of Siegen.

  21. Resnick, S. I. (1971). Tail equivalence and applications,J. Appl. Prob.,8, 136–156.

    Article  MathSciNet  Google Scholar 

  22. Smith, R. L. (1982). Uniform rates of convergence in extreme-value theory,Adv. Appl. Prob.,14, 600–622.

    Article  MathSciNet  Google Scholar 

  23. Weiss, L. (1971). Asymptotic inference about a density function at an end of its range,Naval Res. Logist. Quaterly,18, 111–114.

    Article  MathSciNet  Google Scholar 

  24. Weissman, I. (1975). Multivariate extremal processes generated by independent non-identically distributed random variables,J. Appl. Prob.,12, 477–487.

    Article  MathSciNet  Google Scholar 

  25. Weissman, I. (1978). Estimation of parameters and large quantiles based on thek largest observations,J. Amer. Statist. Ass.,73, 812–815.

    MATH  Google Scholar 

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Falk, M. Rates of uniform convergence of extreme order statistics. Ann Inst Stat Math 38, 245–262 (1986). https://doi.org/10.1007/BF02482514

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  • DOI: https://doi.org/10.1007/BF02482514

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