Soeren I presume what you have is a sort of 'analytical error' for each sample? That is, the standard deviation for two samples at the same location around the 'true value' at the same location?
In this case, you can put the variance down the diagonal of your kriging system to obtain optimal weights under the uncertainty admitted for your data values. You would need to be careful that the 'analytical variance' was not greater than the nugget effect of the semi-variogram model. The kriging system would be similar to that obtained when the sample is not treated as a 'point', but rather as a volume. This results in a lower kriging variance than using zero on the diagonal, so to compensate you should probably add the complete 'analytical variance' back on to get realistic estimation variances. There seems to be a lot of confusion in the books (and software) about what happens if you have a significant replication variance. Isobel Clark http://geoecosse.bizland.com/news.html __________________________________________________ Do You Yahoo!? Everything you'll ever need on one web page from News and Sport to Email and Music Charts http://uk.my.yahoo.com -- * 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
