Hi Maarten, If you have a million times more measurements of a variable A compared to B, the potential improvement will not be depending on the number of additional data you have but obviously on the correlation level between A and B !
You are discussing below the isotopic case of co-kriging (samples at identical locations). There are no differences between ordinary kriging and cokriging if there is no correlation between the two variables (forget then any multivariate approach). Deciding now if your variables are correlated enough (0.3, 0.8 ?) for further use in multivariate geostatistics is another issue. You can play around with transformed data as well to explore the possible correlations. In theory, you will always benefit from co-kriging (independently from the additional costs of doing cross-variography) unless variables have nothing in common. In the case mentioned below (both variables are measured at same locations), think about a situation in which two variables are correlated (due to physical processes) but one shows a high nugget effect and a noisy variogram cloud (e.g. due to problem with measurement technique) while the secondary variable shows a much better structure and low nugget. You will benefit from using your co-variable using cokriging and the estimation variances between ordinary cokriging and ordinary kriging will further help you to assess your gain in using the co-variable: in the worth case scenario, your estimation variance using cokriging will be equal to the one obtained using ordinary kriging. In all the other cases, the estimation variance using cokriging will be lower than the one obtained with ordinary kriging. Check out Pierre Goovaerts'book in which you will find lots of tips on using the various forms of cokriging. Hope this helps (and that my geostatistical "souvenirs" are still correct) Groetjes, Gregoire __________________________________________ Gregoire Dubois (Ph.D.) European Commission (EC) Joint Research Centre Directorate (DG JRC) WWW: http://www.ai-geostats.org "The views expressed are purely those of the writer and may not in any circumstances be regarded as stating an official position of the European Commission." -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Maarten De Boever Sent: 07 June 2006 10:31 To: ai-geostats@jrc.it Subject: AI-GEOSTATS: special case of ordinary cokriging Dear all, The potential improvement of cokriging depends on the extend to which the secondary variable has been sampled additionally to the primary. Is there any difference between ordinary kriging and ordinary cokriging in the situation where all observations of the primary and secondary variable are located at the same locations? Will ordinary cokriging have in that situation any advantage over ordinary kriging? Thanks in advantage, De Boever Maarten. -- ir. Maarten De Boever Research Group Soil Spatial Inventory Techniques (ORBIT) Department Soil Management and Soil Care Faculty of Bioscience Engineering Ghent University Coupure 653, 9000 Gent, Belgium Tel. + 32 (0)9 264 6042 Fax + 32 (0)9 264 6247 e-mail : [EMAIL PROTECTED] http://www.soilman.ugent.be/orbit + + To post a message to the list, send it to ai-geostats@jrc.it To + unsubscribe, send email to majordomo@ jrc.it with no subject and + "unsubscribe ai-geostats" in the message body. DO NOT SEND + Subscribe/Unsubscribe requests to the list As a general service to + list users, please remember to post a summary of any useful responses + to your questions. Support to the forum can be found at + http://www.ai-geostats.org/ + + To post a message to the list, send it to ai-geostats@jrc.it + To unsubscribe, send email to majordomo@ jrc.it with no subject and "unsubscribe ai-geostats" in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list + As a general service to list users, please remember to post a summary of any useful responses to your questions. + Support to the forum can be found at http://www.ai-geostats.org/
