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A Berry-Esseen theorem for the kernel quantile estimator with application to studying the deficiency of quantile estimators

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Abstract

A Berry-Esseen bound is established for the kernel quantile estimator under various conditions. The results improve an earlier result of Falk (1985,Ann. Statist.,13, 428–433) and rely on the local smoothness of the quantile function. This new Berry-Esseen bound is applied to studying the deficiency of the sample quantile estimator with respect to the kernel quantile estimator. A new result is obtained which is an extension of that in Falk (1985).

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References

  • Billingsley, P. (1986).Probability and Measure, 2nd ed., Wiley, New York.

    Google Scholar 

  • Dvoretzky, A., Kiefer, J. and Wolfowitz, J. (1956). Asymptotic minimax character of the sample distribution function and of the classical multinomial estimator,Ann. Math. Statist.,27, 642–669.

    Google Scholar 

  • Falk, M. (1984). Relative deficiency of kernel type estimators of quantiles,Ann. Statist.,12, 261–268.

    Google Scholar 

  • Falk, M. (1985). Asymptotic normality of the kernel quantile estimator,Ann. Statist.,13, 428–433.

    Google Scholar 

  • Feller, W. (1971).An Introduction to Probability Theory and Its Applications, Vol. 2, 2nd ed., Wiley, New York.

    Google Scholar 

  • Friedrich, K. O. (1989). A Berry-Esseen bound for functions of independent random variables,Ann. Statist.,17, 170–183.

    Google Scholar 

  • Gasser, Th. and Müller, H. G. (1984). Estimating regression functions and their derivatives by the kernel method,Scand. J. Statist.,11, 171–185.

    Google Scholar 

  • Helmers, R. and Hušková, M. (1984). A Berry-Esseen bound forL-statistics with unbounded weight functions,Asymptotic Statistics 2, Proceedings of the Third Prague Symposium on Asymptotic Statistics (eds. P. Mandl and M. Hušková), 93–101, North-Holland, Amsterdam.

    Google Scholar 

  • Helmers, R. and van Zwet, W. R. (1982). The Berry-Esseen bound forU-statistics,Statistical Decision Theory and Related Topics, III, Vol. 1 (eds. S. S. Gupta and J. O. Berger), 497–512, Academic Press, New York.

    Google Scholar 

  • Hodges, J. L. and Lehmann, E. L. (1970). Deficiency,Ann. Math. Statist.,41, 783–801.

    Google Scholar 

  • Kaigh, W. D. and Cheng C. (1991). Subsampling quantile estimators and uniformity criteria,Comm. Statist. Theory Methods,20, 539–560.

    Google Scholar 

  • Mammitzsch, V. (1984). On the asymptotically optimal solution within a certain class of kernel type estimators,Statist. Decisions,2, 247–255.

    Google Scholar 

  • Parzen, E. (1979). Nonparametric statistical data modeling,J. Amer. Statist. Assoc.,74, 105–131.

    Google Scholar 

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

    Google Scholar 

  • Reiss, R.-D. (1989).Approximate Distributions of Order Statistics, Springer, New York.

    Google Scholar 

  • Serfling, R. J. (1980).Approximation Theorems of Mathematical Statistics, Wiley, New York.

    Google Scholar 

  • Sheather, S. J. and Marron, J. S. (1990). Kernel quantile estimators,J. Amer. Statist. Assoc.,85, 410–416.

    Google Scholar 

  • Shorack, G. R. and Wellner, J. A. (1986).Empirical Processes with Applications to Statistics, Wiley, New York.

    Google Scholar 

  • Xiang, X. (1993). Deficiency of the sample quantile estimator with respect to the kernel estimators from censored data,Ann. Statist. (to appear).

  • Yang, S. S. (1985). A smooth nonparametric estimator of a quantile function,J. Amer. Statist. Assoc.,80, 1004–1011.

    Google Scholar 

  • Zelterman, D. (1990). Smooth nonparametric estimation of the quantile function,J. Statist. Plann. Inference,26, 339–352.

    Google Scholar 

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Xiang, X. A Berry-Esseen theorem for the kernel quantile estimator with application to studying the deficiency of quantile estimators. Ann Inst Stat Math 47, 237–251 (1995). https://doi.org/10.1007/BF00773460

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  • DOI: https://doi.org/10.1007/BF00773460

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