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Empirical likelihood confidence intervals for the mean of a long‐range dependent process

Author

Listed:
  • Daniel J. Nordman
  • Philipp Sibbertsen
  • Soumendra N. Lahiri

Abstract

. This paper considers blockwise empirical likelihood for real‐valued linear time processes which may exhibit either short‐ or long‐range dependence. Empirical likelihood approaches intended for weakly dependent time series can fail in the presence of strong dependence. However, a modified blockwise method is proposed for confidence interval estimation of the process mean, which is valid for various dependence structures including long‐range dependence. The finite‐sample performance of the method is evaluated through a simulation study and compared with other confidence interval procedures involving subsampling or normal approximations.

Suggested Citation

  • Daniel J. Nordman & Philipp Sibbertsen & Soumendra N. Lahiri, 2007. "Empirical likelihood confidence intervals for the mean of a long‐range dependent process," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(4), pages 576-599, July.
    • Handle: RePEc:bla:jtsera:v:28:y:2007:i:4:p:576-599
    DOI: 10.1111/j.1467-9892.2006.00526.x
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    Cited by:

    1. Feifan Jiang & Lihong Wang, 2018. "Adjusted blockwise empirical likelihood for long memory time series models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 319-332, June.
    2. Gong, Yun & Peng, Liang & Qi, Yongcheng, 2010. "Smoothed jackknife empirical likelihood method for ROC curve," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1520-1531, July.
    3. Chioneso S. Marange & Yongsong Qin & Raymond T. Chiruka & Jesca M. Batidzirai, 2023. "A Blockwise Empirical Likelihood Test for Gaussianity in Stationary Autoregressive Processes," Mathematics, MDPI, vol. 11(4), pages 1-20, February.
    4. Li, Minqiang & Peng, Liang & Qi, Yongcheng, 2011. "Reduce computation in profile empirical likelihood method," MPRA Paper 33744, University Library of Munich, Germany.
    5. Wu, Rongning & Cao, Jiguo, 2011. "Blockwise empirical likelihood for time series of counts," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 661-673, March.
    6. Gianfranco Adimari & Annamaria Guolo, 2010. "A note on the asymptotic behaviour of empirical likelihood statistics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(4), pages 463-476, November.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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