Empirical likelihood confidence intervals for the mean of a long-range dependent process
AbstractThis 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 InfoArticle provided by Wiley Blackwell in its journal Journal of Time Series Analysis.
Volume (Year): 28 (2007)
Issue (Month): 4 (07)
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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782
Other versions of this item:
- Nordman, Dan Nordman & Sibbertsen, Philipp & Lahiri, Soumendra N., 2005. "Empirical likelihood confidence intervals for the mean of a long-range dependent process," Diskussionspapiere der Wirtschaftswissenschaftlichen FakultÃ¤t der Leibniz UniversitÃ¤t Hannover dp-327, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
- 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
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