Ive been a lurker for a while, and have learned a lot from reading the discussions, so thanks in advance for that.
My question concerns the use of the normal score transform when making repeated conditional sequential Gaussian simulations using GSLIB. I believe the criticism that the backtransform would give biased results (as discussed in the Saito and Goovaerts 2000 paper in the discussion about Multi-Gausinan Kriging) does not apply to simulations because at each point to be simulated, a single normal score value is drawn at random from the cdf obtained by kriging. The averaging takes place in the original data space. I came to this conclusion from trying to figure out how I could apply the correction described in the Saito and Goovaerts paper. But even if the above is true, I may still have a problem because of the high percentage of zeros in my data sets, which ranges from 4 to 22%. I (the GSLIB program actually) rank these zero values randomly and I dont know how to implement the suggestion (of Goovaerts, citing Verly 1986) of ranking them based on the average value in a search radius so that zeros near high densities have higher ranks than those in low density areas. For my purposes, I calculate the total abundance for each realization, and use the frequency distribution of these totals to calculate empirical confidence intervals, so Im mostly interested in the variability in these total abundance realizations. How would the zeros affect this? Someone has suggested that doing the ranking randomly would increase the nugget effect of the normal score variograms. However, I have 6 data sets and the ones with the highest % of zeros are not the ones with the largest nuggets. If the nugget has been artificially inflated because zeros are not correlated after nscore transform when in fact they are correlated in the raw data space, is it reasonable to say that the variability of the simulated total abundances would be overestimated (and thus conservative)? Cheers, Paul Walline NOAA Fisheries, Alaska Fisheries Science Center
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