, Volume 8, Issue 1, pp 95-116

An overview of bootstrap methods for estimating and predicting in time series

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Abstract

In this paper an overview of the existing literature about bootstrapping for estimation and prediction in time series is presented. Some of the methods are detailed, organized according to the aim they are designed for (estimation or prediction) and to the fact that some parametric structure is assumed, or not, for the dependence. Finally, some new bootstrap (kernel based) method is presented for prediction when no parametric assumption is made for the dependence.

This research was partially supported by the “Dirección General de Investigación Científica y Tćnica” Grants PB94-0494 and PB95-0826 and by the “Xunta de Galicia” Grant XUGA 10501B97.