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Bootstrapping the sample means for stationary mixing sequences

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  • Shao, Qi-Man
  • Yu, Hao

Abstract

We propose a circular block resampling procedure to modify Künsch's moving block bootstrap. Our procedure has the special feature that the resampled data are like drawing from the empirical distribution function of dependent observations. No information is lost concerning the nature of dependency of the original observations coming from a general stationary sequence. We prove two general theorems on bootstrapping sample means for stationary sequences. Applications to stationary [alpha]-mixing, [rho]-mixing and [phi]-mixing sequences are also discussed.

Suggested Citation

  • Shao, Qi-Man & Yu, Hao, 1993. "Bootstrapping the sample means for stationary mixing sequences," Stochastic Processes and their Applications, Elsevier, vol. 48(1), pages 175-190, October.
    • Handle: RePEc:eee:spapps:v:48:y:1993:i:1:p:175-190
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    Citations

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    Cited by:

    1. Ardia, David & Hoogerheide, Lennart F., 2014. "GARCH models for daily stock returns: Impact of estimation frequency on Value-at-Risk and Expected Shortfall forecasts," Economics Letters, Elsevier, vol. 123(2), pages 187-190.
    2. Fan, Jianqing & Han, Fang & Liu, Han & Vickers, Byron, 2016. "Robust inference of risks of large portfolios," Journal of Econometrics, Elsevier, vol. 194(2), pages 298-308.
    3. Psaradakis, Zacharias, 2001. "On bootstrap inference in cointegrating regressions," Economics Letters, Elsevier, vol. 72(1), pages 1-10, July.
    4. 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.
    5. Dehling, Herold & Fried, Roland & Sharipov, Olimjon Sh. & Vogel, Daniel & Wornowizki, Max, 2013. "Estimation of the variance of partial sums of dependent processes," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 141-147.
    6. Alonso Fernández, Andrés Modesto & Peña, Daniel & Romo, Juan, 2000. "Resampling time series by missing values techniques," DES - Working Papers. Statistics and Econometrics. WS 9923, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Dehling, Herold & Sharipov, Olimjon Sh. & Wendler, Martin, 2015. "Bootstrap for dependent Hilbert space-valued random variables with application to von Mises statistics," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 200-215.
    8. Hwang, Eunju & Shin, Dong Wan, 2012. "Strong consistency of the stationary bootstrap under ψ-weak dependence," Statistics & Probability Letters, Elsevier, vol. 82(3), pages 488-495.
    9. Zacharias Psaradakis, 2008. "Assessing Time‐Reversibility Under Minimal Assumptions," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 881-905, September.
    10. Olimjon Sharipov & Martin Wendler, 2012. "Bootstrap for the sample mean and for -statistics of mixing and near-epoch dependent processes," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(2), pages 317-342.
    11. Andrés Alonso & Daniel Peña & Juan Romo, 2003. "Resampling time series using missing values techniques," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(4), pages 765-796, December.
    12. Xin Chen & Jieli Ding & Liuquan Sun, 2018. "A semiparametric additive rate model for a modulated renewal process," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(4), pages 675-698, October.
    13. Csörgo, Miklós & Yu, Hao, 1997. "Estimation of total time on test transforms for stationary observations," Stochastic Processes and their Applications, Elsevier, vol. 68(2), pages 229-253, June.
    14. Sharipov, Olimjon Sh. & Wendler, Martin, 2013. "Normal limits, nonnormal limits, and the bootstrap for quantiles of dependent data," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1028-1035.

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