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