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Subsampling the mean of heavy-tailed dependent observations
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Abstract
We establish the validity of subsampling confidence intervals for the mean of a dependent series with heavy-tailed marginal distributions. Using point process theory, we study both linear and nonlinear GARCH-like time series models. We propose a data-dependent method for the optimal block size selection and investigate its performance by means of a simulation study.Heavy tails, linear time series, subsampling