In your example (8:00) of a hypothetical variogram....I don't get the logic of A correlated to B, B correlated to C but A not correlated to C. Logically speaking: If A is correlated to B then B must also be Correlated to A, and if B is correlated to C then C must also be correlated to A (since B is correlated to C and B is correlated to A)....its a bit of a hurdle in understanding the paradox :-) Thank you so much for posting these lectures....I find them extremely useful.
At the 16:15 min mark. The exponential variogram should have a formula which is akin to gamma(h) = c1*(1-exp(-3*h/a)) Please let me know if that is correct, I am just guessing from the other info that you are showing (mostly the slope of 1/3)
Hi Dr. Michael. I have a question if you have time. Each cell should have one value representing the property e.g. porosity, so how do you sum the two structures? i.e. how do you superimpose the two structures to get the nested structure? or you just create a new dataset with these two structures characteristics embedded in the new structure?
In the two examples at the end, the vertical range was 8 throught the different structure even in thr range of 0.8 to 1 of the variogram value. Whereas in the second example it was 20 in the 0.8 to 1 bracket and 6 before, why the difference?
That will depend on the model you adjusted to your semivariogram. The nugget effect would be the value which your variogram model "touches" the semivariance axis.
In your example (8:00) of a hypothetical variogram....I don't get the logic of A correlated to B, B correlated to C but A not correlated to C. Logically speaking: If A is correlated to B then B must also be Correlated to A, and if B is correlated to C then C must also be correlated to A (since B is correlated to C and B is correlated to A)....its a bit of a hurdle in understanding the paradox :-) Thank you so much for posting these lectures....I find them extremely useful.
Michael,Jeff, deutsch, you all are the best geostatistic teacher, Thanks for your precious courses
Great lecture! I can finally understand nested variogram model. Thanks Michael.
At the 16:15 min mark. The exponential variogram should have a formula which is akin to
gamma(h) = c1*(1-exp(-3*h/a))
Please let me know if that is correct, I am just guessing from the other info that you are showing (mostly the slope of 1/3)
Hi Dr. Michael. I have a question if you have time. Each cell should have one value representing the property e.g. porosity, so how do you sum the two structures? i.e. how do you superimpose the two structures to get the nested structure? or you just create a new dataset with these two structures characteristics embedded in the new structure?
Hi professor for the sill in variogram models do we use variance for sill? how do we calculate sill
In the two examples at the end, the vertical range was 8 throught the different structure even in thr range of 0.8 to 1 of the variogram value. Whereas in the second example it was 20 in the 0.8 to 1 bracket and 6 before, why the difference?
If the semivariogram value at the smallest lag distance (say, 50m) is 0.3, what should the nuggest effect be? 0.3 or
That will depend on the model you adjusted to your semivariogram. The nugget effect would be the value which your variogram model "touches" the semivariance axis.