NDLI: Robust Resampling Confidence Intervals for Empirical Variograms

Content Provider	Springer Nature Link
Author	Clark, Robert Graham Allingham, Samuel
Copyright Year	2010
Abstract	The variogram function is an important measure of the spatial dependencies of a geostatistical or other spatial dataset. It plays a central role in kriging, designing spatial studies, and in understanding the spatial properties of geological and environmental phenomena. It is therefore important to understand the variability attached to estimates of the variogram. Existing methods for constructing confidence intervals around the empirical variogram either rely on strong assumptions, such as normality or known variogram function, or are based on resampling blocks and subject to edge effect biases. This paper proposes two new procedures for addressing these concerns: a quasi-block-bootstrap and a quasi-block-jackknife. The new methods are based on transforming the data to decorrelate it based on a fitted variogram model, resampling blocks from the decorrelated data, and then recorrelating. The coverage properties of the new confidence intervals are compared by simulation to a number of existing resampling-based intervals. The proposed quasi-block-jackknife confidence interval is found to have the best properties of all of the methods considered across a range of scenarios, including normally and lognormally distributed data and misspecification of the variogram function used to decorrelate the data.
Starting Page	243
Ending Page	259
Page Count	17
File Format	PDF
ISSN	18748961
Journal	Mathematical Geosciences
Volume Number	43
Issue Number	2
e-ISSN	18748953
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-12-03
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Spatial analysis Variograms Bootstrap Jackknife Block bootstrap Block jackknife Hydrogeology Geotechnical Engineering Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Mathematical Applications in Earth Sciences
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Mathematics

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