On Wed, 2003-07-09 at 10:06, Gregoire Dubois wrote: > I'm surprised we got mainly "pragmatic" answers to your question and > would have expected from statisticians and mathematicians more reactions > about a possible statistical heresy: the semivariogram model is fitted to an > experimental semivariogram which was obtained from a certain number of points. > To be mathematically correct in terms of the various hypotheses used, should > one not use a search neighbourhood that is equal to the one used to obtain the > semivariogram (frequently all points) ?
I agree. But then you need to model the experimental semivariogram for all distances. Wouldn't this be a problem to find a reliable model fit? > On the other hand, if the main objective is to compare various algorithms > (e.g. ordinary kriging versus indicator kriging, or indicator kriging versus > log-kriging) or kriging variances obtained by various models, I would imagine > that using a "no search" approach (all neighbours are used) would be the most > reasonable approach... The objective is to compare different algorithms AND create a most realistic map at the same time by using these algorithms. So I guess there have to made some compromises. Probably cross-validation could help if I use a sub set of the data set. Ulrich -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
