Journal of the Southern African Institute of Mining and Metallurgy
On-line version ISSN 2411-9717
Print version ISSN 0038-223X
OLEA, R.A.; PARDO-IGUZQUIZA, E. and DOWD, P.A.. Robust and resistant semivariogram modelling using a generalized bootstrap. J. S. Afr. Inst. Min. Metall. [online]. 2015, vol.115, n.1, pp.37-44. ISSN 2411-9717.
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.
Keywords : geostatistics; sampling distribution; median; normal score transformation; ordinary least-squares fitting.