Hi,
There will certainly be situations when the SS method will select an
appropriate model. But there are also situations when it will not make a
well thought over decision. For example if there is not a lot of data on
short range variability the SS method will not be able to fit the model
that shows the appropriate short range behaviour.
You spoke of more sophisticated methods of automatically choosing
between models, what kind of methods did you have in mind?
cheers,
Paul
G. Allegri schreef:
At this stage I do
this by computing the sums of squares between the model and the sample
variogram and choose the one with the smallest SS. This is a rather crude
way of selecting between the models.
Thanks Paul for automap. I'm planning to try it in the next occasion.
What are the major drawbacks in using simply SS in model selection? I
mean, I know there are lot of more sofiticated methods, but is this
good for some situation, or is in general a poor selection method?
thanks,
Giovanni
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