Dan Nordman

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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(More)
The sampling window method of Hall, Jing and Lahiri (1998) is known to consistently estimate the distribution of the sample mean for a class of long-range dependent processes, generated by transformations of Gaussian time series. This note shows that the same non-parametric subsampling method is also valid for an entirely different category of long-range(More)
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