Abstract

Most 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 also be employed for different types of non-stationarity data. Consistency of estimators are demonstrated under mild moment and mixing conditions. Rates of convergence are provided, giving guidance for the appropriate choice of subshape size. Results from a small simulation study on finite-sample properties are also reported.

Keywords

block bootstrap; mixing; non-stationary random field; resampling; spatial lattice data; subsampling

Published in

Scandinavian Journal of Statistics
2008, Volume: 35, number: 1, pages: 38-63

SLU Authors

• Ekström, Magnus

  • Department of Forest Economics, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Probability Theory and Statistics


Publication identifier

DOI: https://doi.org/10.1111/j.1467-9469.2007.00572.x

Permanent link to this page (URI)

https://res.slu.se/id/publ/19232