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

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Author Info

  • 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. Copyright 2007 The Authors Journal compilation 2007 Blackwell Publishing Ltd.

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Bibliographic Info

Article provided by Wiley Blackwell in its journal Journal of Time Series Analysis.

Volume (Year): 28 (2007)
Issue (Month): 4 (07)
Pages: 576-599

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Handle: RePEc:bla:jtsera:v:28:y:2007:i:4:p:576-599

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References

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  1. Davidson, James & Sibbertsen, Philipp, 2009. "Tests of bias in log-periodogram regression," Economics Letters, Elsevier, vol. 102(2), pages 83-86, February.
  2. ANDREWS, DONALD W & Sun, Yixiao X, 2002. "Adaptive Local Polynomial Whittle Estimation of Long-Range Dependence," University of California at San Diego, Economics Working Paper Series qt9wt048tt, Department of Economics, UC San Diego.
  3. Nordman, Daniel J. & Lahiri, Soumendra N., 2005. "Validity Of The Sampling Window Method For Long-Range Dependent Linear Processes," Econometric Theory, Cambridge University Press, vol. 21(06), pages 1087-1111, December.
  4. Lahiri, S. N., 1993. "On the moving block bootstrap under long range dependence," Statistics & Probability Letters, Elsevier, vol. 18(5), pages 405-413, December.
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Cited by:
  1. Hjort, Nils Lid, 2009. "Extending the Scope of Empirical Likelihood. Ann. Stat," Open Access publications from Université catholique de Louvain info:hdl:2078.1/35625, Université catholique de Louvain.
  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. Li, Minqiang & Peng, Liang & Qi, Yongcheng, 2011. "Reduce computation in profile empirical likelihood method," MPRA Paper 33744, University Library of Munich, Germany.
  4. 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.
  5. Gianfranco Adimari & Annamaria Guolo, 2010. "A note on the asymptotic behaviour of empirical likelihood statistics," Statistical Methods and Applications, Springer, vol. 19(4), pages 463-476, November.

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