RE: AI-GEOSTATS: special case of ordinary cokriging

2006-06-07 Thread Gregoire Dubois
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 


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RE: AI-GEOSTATS: special case of ordinary cokriging

2006-06-07 Thread Pierre Goovaerts
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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