Two-point declustering for weighting data pairs in experimental variogram calculations ?
The primary goal of calculating experimental variograms in kriging studies is to estimate the required variogram model. The destructuring effect of preferentially clustered data on the sample variogram is well-known but rarely considered in their experimental calculation and modelling due to a lack of suitable two-point declustering methods. This paper presents two methods of declustering that can be used to weight data pairs in experimental variogram calculations. Firstly, the traditional cell declustering method is extended to the two-point case, and secondly, data location clusters are identified and then explicitly used to determine declustering weights for data pairs. Experimental variograms calculated for a small, preferentially clustered and strongly positively skewed dataset show structural improvement when the two-point declustering weights are considered, resulting in significant changes to the estimated variogram model. Computer programs that implement the proposed two-point declustering and experimental variogram weighting techniques are presented.
kriging destructuring effect variogram estimation spatial structures geostatistics