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The block bootstrap has been largely developed for weakly dependent time processes and, in this context, much research has focused on the large-sample properties of block bootstrap inference about sample means. This work validates the block bootstrap for distribution estimation with stationary, linear processes exhibiting strong dependence. For estimating the sample mean’s variance under long-memory,...
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