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- Description: Sequential Gaussian Simulation algorithm explained: During prediction of the value of Cell 1 (C1) no data points are found within the range (note, the value of C2 has not been estimated yet). The range is governed by the variogram and indicates the point at which data shows no correlation (or where the semi-variance vs distance plot starts to flatten). Because no data exists whithin the range a random value is pickid from the data's histogram for the C1 cell. When the C2 cell is now visited the C1 cell and the other datapoints (two green and one yellow) are also used. Their relative weight is based on the variogram. The grey datapoint is only used to for the histogram, but is not used directly for estimating the point C1 and C2. The SGS algorithm will thus generate a (equiprobable) unique outcome each time, but when run thousands of times and when taking the average of all these realisations you will achieve the same result as kriging.
- Words in this image: random, histogram, semi-variance, variogram, range, sample weight, distance, cell, SGS, sequential Gaussian Simulation, Random Function Simulation, cell visitation order
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