Block Sampling under Strong Dependence
classification
🧮 math.ST
q-fin.STstat.TH
keywords
processesblocksamplingdependencelahirilinearmethodunder
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The paper considers the block sampling method for long-range dependent processes. Our theory generalizes earlier ones by Hall, Jing and Lahiri (1998) on functionals of Gaussian processes and Nordman and Lahiri (2005) on linear processes. In particular, we allow nonlinear transforms of linear processes. Under suitable conditions on physical dependence measures, we prove the validity of the block sampling method. The problem of estimating the self-similar index is also studied.
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