Hello,
 
In general, the primary data will screen the influence of the co-located 
secondary data,
leading to the similarity of the results provided by isotopic cokriging and 
kriging ignoring this
secondary information; see my paper in Math Geol. 
 Goovaerts, P. 1998. Ordinary cokriging revisited. Mathematical Geology, 30(1): 
21-42. 
 
However, in some situations it is the secondary data that will screen the 
influence
of primary data. It is likely to happen when both variables are strongly 
correlated and
the secondary variable varies more continuously in space than the primary 
variable,
i.e. the secondary variogram has a smaller nugget effect.. See the example in 
my book 
pages 219-220.
 
Cheers,
 
Pierre
 
 
Pierre Goovaerts
Chief Scientist at BioMedware Inc.
Courtesy Associate Professor, University of Florida
President of PGeostat LLC
 
Office address: 
516 North State Street
Ann Arbor, MI 48104
Voice: (734) 913-1098 (ext. 8)
Fax: (734) 913-2201 
http://home.comcast.net/~goovaerts/ 

________________________________

From: [EMAIL PROTECTED] on behalf of Maarten De Boever
Sent: Wed 6/7/2006 4:30 AM
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


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