Subsampling for general statistics under long range dependence

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Date

2015

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Abstract

In the statistical inference for long range dependent time series, the shape of the limit distribution typically dependents on unknown param- eters. Therefore, we propose to use subsampling. We show the validity of subsampling for general statistics and long range dependent subordinated Gaussian processes, which satisfy mild regularity conditions. We apply our method to a self-normalized change-point test statistic and investigate the finite sample properties in a simulation study.

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Keywords

subsampling, change point test, long range dependence, Gaussian processes

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