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U-processes, U-quantile processes and generalized linear statistics of dependent data

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  • Wendler, Martin

Abstract

Generalized linear statistics are a unifying class that contains U-statistics, U-quantiles, L-statistics as well as trimmed and Winsorized U-statistics. For example, many commonly used estimators of scale fall into this class. GL-statistics have only been studied under independence; in this paper, we develop an asymptotic theory for GL-statistics of sequences which are strongly mixing or L1 near epoch dependent on an absolutely regular process. For this purpose, we prove an almost sure approximation of the empiricalU-process by a Gaussian process. With the help of a generalized Bahadur representation, it follows that such a strong invariance principle also holds for the empirical U-quantile process and consequently for GL-statistics. We obtain central limit theorems and laws of the iterated logarithm for U-processes, U-quantile processes and GL-statistics as straightforward corollaries.

Suggested Citation

  • Wendler, Martin, 2012. "U-processes, U-quantile processes and generalized linear statistics of dependent data," Stochastic Processes and their Applications, Elsevier, vol. 122(3), pages 787-807.
    • Handle: RePEc:eee:spapps:v:122:y:2012:i:3:p:787-807
    DOI: 10.1016/j.spa.2011.11.010
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    References listed on IDEAS

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    1. Babu, Gutti Jogesh & Singh, Kesar, 1978. "On deviations between empirical and quantile processes for mixing random variables," Journal of Multivariate Analysis, Elsevier, vol. 8(4), pages 532-549, December.
    2. Hansen, Bruce E., 1991. "GARCH(1, 1) processes are near epoch dependent," Economics Letters, Elsevier, vol. 36(2), pages 181-186, June.
    3. Wendler, Martin, 2011. "Bahadur representation for U-quantiles of dependent data," Journal of Multivariate Analysis, Elsevier, vol. 102(6), pages 1064-1079, July.
    4. Arcones, Miguel A. & Giné, Evarist, 1995. "On the law of the iterated logarithm for canonical U-statistics and processes," Stochastic Processes and their Applications, Elsevier, vol. 58(2), pages 217-245, August.
    5. Dehling, Herold & Wendler, Martin, 2010. "Central limit theorem and the bootstrap for U-statistics of strongly mixing data," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 126-137, January.
    6. Arcones, M. A., 1993. "The Law of the Iterated Logarithm for U-Processes," Journal of Multivariate Analysis, Elsevier, vol. 47(1), pages 139-151, October.
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    Cited by:

    1. Tarr, G. & Weber, N.C. & Müller, S., 2015. "The difference of symmetric quantiles under long range dependence," Statistics & Probability Letters, Elsevier, vol. 98(C), pages 144-150.

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