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We derive an approximation of a density estimator based on weakly dependent random vectors by a density estimator built from independent random vectors. We construct, on a suuciently rich probability space, such a pairing of the random variables of both experiments that the set of observations fX 1 ; : : : ; X n g from the time series model is nearly the… (More)

Degenerate U-and V-statistics play an important role in the field of hypothesis testing since numerous test statistics can be formulated in terms of these quantities. Therefore, consistent bootstrap methods for U-and V-statistics can be applied in order to approximate critical values of those tests. First, we prove a new asymptotic result for degenerate… (More)

Knowledge about the distribution of a statistical estimator is important for various purposes, such as the construction of confidence intervals for model parameters or the determination of critical values of tests. A widely used method to estimate this distribution is the so-called boot-strap, which is based on an imitation of the probabilistic structure of… (More)

- Paul Doukhan, Michael H Neumann
- 2006

We give an introduction to a notion of weak dependence which is more general than mixing and allows to treat for example processes driven by discrete innovations as they appear with time series bootstrap. As a typical example, we analyze autoregressive processes and their bootstrap analogues in detail and show how weak dependence can be easily derived from… (More)

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