Robust and resistant semivariogram modelling using a generalized bootstrap

Journal of the Southern African Institute of Mining and Metallurgy
By: , and 

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Abstract

The bootstrap is a computer-intensive resampling method for estimating
the uncertainty of complex statistical models. We expand on an
application of the bootstrap for inferring semivariogram parameters and
their uncertainty. The model fitted to the median of the bootstrap distribution
of the experimental semivariogram is proposed as an estimator of
the semivariogram. The proposed application is not restricted to normal
data and the estimator is resistant to outliers. Improvements are more
significant for data-sets with less than 100 observations, which are
those for which semivariogram model inference is the most difficult. The
application is illustrated by using it to characterize a synthetic random
field for which the true semivariogram type and parameters are known.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Robust and resistant semivariogram modelling using a generalized bootstrap
Series title Journal of the Southern African Institute of Mining and Metallurgy
Volume 115
Issue 1
Year Published 2015
Language English
Publisher Southern African Institute of Mining and Metallurgy (SAIMM)
Contributing office(s) Eastern Energy Resources Science Center
Description 8 p.
First page 37
Last page 44
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