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

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  • 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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  1. Lahiri, S. N., 1993. "On the moving block bootstrap under long range dependence," Statistics & Probability Letters, Elsevier, Elsevier, vol. 18(5), pages 405-413, December.
  2. Donald W. K. Andrews & Yixiao Sun, 2004. "Adaptive Local Polynomial Whittle Estimation of Long-range Dependence," Econometrica, Econometric Society, Econometric Society, vol. 72(2), pages 569-614, 03.
  3. Davidson, James & Sibbertsen, Philipp, 2005. "Tests of Bias in Log-Periodogram Regression," Hannover Economic Papers (HEP), Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät dp-317, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  4. Nordman, Daniel J. & Lahiri, Soumendra N., 2005. "Validity Of The Sampling Window Method For Long-Range Dependent Linear Processes," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 21(06), pages 1087-1111, December.
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Cited by:
  1. Wu, Rongning & Cao, Jiguo, 2011. "Blockwise empirical likelihood for time series of counts," Journal of Multivariate Analysis, Elsevier, Elsevier, vol. 102(3), pages 661-673, March.
  2. Gianfranco Adimari & Annamaria Guolo, 2010. "A note on the asymptotic behaviour of empirical likelihood statistics," Statistical Methods and Applications, Springer, Springer, vol. 19(4), pages 463-476, November.
  3. Gong, Yun & Peng, Liang & Qi, Yongcheng, 2010. "Smoothed jackknife empirical likelihood method for ROC curve," Journal of Multivariate Analysis, Elsevier, Elsevier, vol. 101(6), pages 1520-1531, July.
  4. Li, Minqiang & Peng, Liang & Qi, Yongcheng, 2011. "Reduce computation in profile empirical likelihood method," MPRA Paper 33744, University Library of Munich, Germany.

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