, Volume 8, Issue 1, pp 95–116

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


DOI: 10.1007/BF02595864

Cite this article as:
Cao, R. Test (1999) 8: 95. doi:10.1007/BF02595864


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.

Key Words

Autoregressive processesblockwise bootstrapmoving average processesmoving blocks bootstrapresampling methodsstationary bootstrap

AMS subject classification

Primary 62G09secondary 62G0762M1062M2060G25

Copyright information

© Sociedad Española de Estadistica e Investigación Operativa 1999

Authors and Affiliations

  1. 1.Departamento de MatemáticasUniversidade da CoruñaA CoruñaSpain