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AI-GEOSTATS: Cokriging Estimation Variances

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  • Sylvester, Sharron
    Hi I have calculated estimates of my Primary variable every 1m over a grid of 60 x 60 x 1m (i.e. 3,600 estimates) using traditional ordinary cokriging. I am
    Message 1 of 1 , Oct 28, 2001
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      Hi

      I have calculated estimates of my Primary variable every 1m over a grid of
      60 x 60 x 1m (i.e. 3,600 estimates) using traditional ordinary cokriging. I
      am using a 20 x 20m search for the Primary variable and 18 x 18m for the
      Secondary variable, and a minimum of 4, maximum of 12 Primary and Secondary
      samples.

      I have 200 Primary samples, which are not gridded and are fairly evenly
      distributed across the location. My Primary variable has a variance of
      ~600.

      I have 300 Secondary data - 200 of which are 'co-located' with the Primary
      variable, and the other 100 are 'independent' of the Primary dataset and are
      also fairly evenly scattered across the location. My Secondary variable has
      a variance of ~4.0.

      My coregionalisation matrix satisfies the positive semi-definite
      requirement, (with one zero eigenvalue in the nugget variance matrix)

      My query relates to the pattern of estimation variances - I get 200 zero
      variances at the Primary Sample locations (this I understand) - what I do
      not understand is that I get 100 moderate estimation variances of
      approximately ~1150 (1153 - 1160) at the 100 Secondary sample locations
      without accompanying Primary values , and every other variance in the
      location is the same value (2650).

      Is this a sign that I am doing something wrong as I would have expected that
      a non-gridded dataset would not give a constant estimation variance at
      locations away from the sample locations? Is this phenomenon likely to be
      exclusive to cokriging as I have not struck it before except in totally
      gridded data.

      Regards

      Sharron Sylvester

      EOM

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