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Re: AI-GEOSTATS: Kt estimation variance

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  • Isobel Clark
    Sebastiano Large kriging variances have nothing to do with negative weights. The two are completely different phenomena - especially in Universal Kriging. In
    Message 1 of 2 , Oct 24, 2003
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      Sebastiano

      Large kriging variances have nothing to do with
      negative weights. The two are completely different
      phenomena - especially in Universal Kriging.

      In Ordinary Kriging the estimation variance can become
      as high as two times the total sill of the
      semi-variogram. This is a theoretical fact(?) and you
      can derive the answer by simply trying to estimate the
      value at one point from a single sample at or beyond
      the range of influence from this location. That is, a
      weight of +1!!

      In Universal Kriging, the weights often become
      negative because the system is trying to force the
      estimated point to lie on the trend of the samples.
      Sometimes it can only do this by using negative
      weights. There is no problem here, unless you have
      extremely high 'erratic' residuals. In this case, you
      should probably resolve that problem before trying
      kriging.

      If the variance becomes very high in Universal Kriging
      it is probably because you are extrapolating into
      sparsely sampled areas. Remember you are trying to
      estimate the trend as well as the 'residual' value and
      this contributes to higher variances. You should widen
      your search radius to include more samples than with
      Ordinary Kriging.

      You can see how all this works with our free kriging
      game. If your data is in Geo-EAS form or a simple CSV
      file, you can read it into Krigame and see the
      equations and the solutions. Then vary search
      parameters etc to see how they are affected. You might
      want to download our Tutorial 3 which discusses
      Universal Kriging with the Wolfcamp data.

      All available at
      http://geoecosse.bizland.com/softwares with no
      restriction on use or distribution.

      Isobel

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