Abstract

Most of the proposed subsampling and resampling methods in the literature assume stationary data. In many empirical applications, however, the hypothesis of stationarity can easily be rejected. In this paper we demonstrate that moment and variance estimators based on the subsampling methodology can be employed also for di®erent types of nonstationarity data. Consistency of estimators are demonstrated under mild moment and mixing conditions. Rates of convergence are provided, giving guidance into the appropriate choice of subshape size. Results from a small simulation study on finite sample properties are also reported

Keywords

Subsampling; resampling; block bootstrap; nonstationary random field; spatial lattice data; mixing

Published in

Research report (Centre of Biostochastics)
2005, Volume: 2005, number: 7, pages: 1-27
Publisher: SLU

SLU Authors

• Ekström, Magnus

  • Department of Forest Economics, Swedish University of Agricultural Sciences
    

Permanent link to this page (URI)

https://res.slu.se/id/publ/6847