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Subsampling variance estimation for nonstationary spatial lattice data
Centre of Biostochastics, Swedish University of Agricultural Sciences, Umeå.
2008 (English)In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 35, no 1, 38-63 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Wiley-Blackwell, 2008. Vol. 35, no 1, 38-63 p.
Keyword [en]
block bootstrap, mixing, non-stationary random field, resampling, spatial lattice data, subsampling
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:umu:diva-81153DOI: 10.1111/j.1467-9469.2007.00572.xOAI: oai:DiVA.org:umu-81153DiVA: diva2:653028
Available from: 2013-10-02 Created: 2013-10-02 Last updated: 2017-12-06Bibliographically approved

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Ekström, Magnus

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