Note that gamma(V,V) is a variogram model property, not a data property: in the figure you mention, the big dots are data points, the small dots discretize the block but do not indicate observed data.
I know that you can discretize block estimates with a pretty good accuracy with a limited amount of points. But, I was convinced that I could use grided observed data and gamma(V,V) as an estimate for the variance within my grided block.
To clarify,
I did measure the point values in a grid in a plot/block. I don't have to estimate them, I just need a spacially depended estimate of the whole plot/block variance.
The problem is that I would like to automate the procedure of calculating that within block variance because variogram models need to be fit visually most of the time, wich is time consuming. When repeating calculations on randomized data this isn't an option. So if gamma(V,V) really is model property rather then a data property I have a problem...
If you can see the trees for the forest, because I don't. Koen.
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