Skip to main content
SLU publication database (SLUpub)

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 talk, it is demonstrated that variance estimators based on the subsampling methodology can be employed for different types of nonstationarity data, and the estimators are shown to be consistent under mild moment and mixing conditions. Results from a small simulation study on finite sample properties are provided, and an example with applications to forestry, using satellite data, is discussed

Conference

Exploring Stochastics

SLU Authors

UKÄ Subject classification

Probability Theory and Statistics

Permanent link to this page (URI)

https://res.slu.se/id/publ/21578