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Re: GEOSTATS: Linear Model of Coregionalization -- Devil's Advocate

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  • Denis ALLARD
    ... Hello Todd, it seems to me that if you seek a minimum variance estimator, an important constraint is that your variance MUST be non negative ! In this
    Message 1 of 6 , Jun 7, 1999
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      On Fri, 4 Jun 1999, Todd Mowrer wrote:

      > question is: What is the consequence of negative cokriging variances?
      > Does one no longer have a best linear unbiased estimator? It would seem
      > to me that one would still obtain a minimum variance (from the
      > semi-variogram) weighted combination of measured values to estimate
      > unknown locations. If you don't use cokriging variances for anything,
      > e.g., co-conditional simulation, (or even look at them, much less
      > mention them ), why care?


      Hello Todd,

      it seems to me that if you seek a minimum variance estimator, an important
      constraint is that your variance MUST be non negative ! In this case, a
      null variance would mean exact interpolation, as it is the case when
      kriging at a data point (kriging is an exact interpolator). If you allow
      negative variance, there is no minimum anymore, or more exactly the
      theoretical minimum variance is - infinity !!!!

      Now, if you don't care about kriging variances, and don't even look at
      them, wht bother with a statistical, probability based, approach ?
      Why don't you use any interpolation package ?

      The main point of geostatistics, vs mere interpolation is that it provides
      a measure of the estimation uncertainty (the kriging variance) along
      with the interpolation itself, at the cost of a model -- the variogram(s).

      For me, mismodeling the variogram and ignoring the kriging variance is
      simply missing the point.



      Denis Allard


      .------------------------Denis ALLARD--------------------------------.
      | Unite de Biometrie allard@... |
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    • Octavi Fors Aldrich
      Hello everybody, I m novice using GSLIB2, and after taking a quicklook in the User s Guide, I ve missed one capability in gamv.f program. When calculating
      Message 2 of 6 , Jun 9, 1999
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        Hello everybody,

        I'm novice using GSLIB2, and after taking a quicklook in the User's Guide,
        I've missed one capability in gamv.f program. When calculating variogram
        gamma(h) (whatever option you choose) it could be interesting to have h
        as a non-equally distributed distances array. Unfortunately, it
        seems that gamv.f outputs h as an equally-grided one. This is not
        important when number of points per lag is high, but not the same when
        it's low.

        I was wondering if anybody has "patched" this issue by adding some
        code lines to gamv.f. Any experiences?

        Thanks in advance,

        Octavi.

        =================================================================

        Octavi Fors Aldrich

        Astronomy Department
        Physics Faculty
        Avgda. Diagonal 647
        08028 Barcelona
        SPAIN

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      • Ulrich Leopold
        Hi all, I have some question concerning the modeling. I have calculated different variogram estimators. The traditional semivariogram reveals spatial
        Message 3 of 6 , Jun 10, 1999
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          Hi all,

          I have some question concerning the modeling.

          I have calculated different variogram estimators.
          The traditional semivariogram reveals spatial continuity. But the
          shape, the ranges and anisotropies are better estimated by the more
          robust pairwise relative semivariogram.

          My questions are:

          (1) Could I model the experimental pairwise relative semivariogram
          (or other more robust variograms) or does it affect the
          kriging estimator and it's estimation variance considering the
          accuracy? And if yes do I have to standardize the sill to one?

          (2) Is there a difference between modeling the traditional
          semivariogram with it's original sill value and with a sill
          standardized to one.

          (3) What is really necessary to yield the correct estimates? Only the
          ratios of nugget and sill structures and their corresponding ranges
          or the real values provided by the traditional semivariogram with a
          non standardized sill?

          Goovaerts 1997 ("Geostatistics for natural resources estimation")
          warns against using the more robust estimators as substitutes for
          the traditional semivariogram. But for example Srivastava and Parker
          1989 ("Robust measures of spatial continuity") did model several
          robust estimators besides the traditional semivariogram.

          If a robust measure provides a better spatial continuity I would say
          that I can use it for modeling. Only the estimation variance will be
          affected and should not be taken as an absolute value but used in
          relative terms to compare the variances.


          Thanks in advance

          Ulrich

          ><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

          Ulrich Leopold

          Department of Soil Science
          The University of Trier

          E-mail: leop6101@...
          phone: 0049-(0)651-140764
          address: Engelstr.104, 54292 Trier, Germany
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        • Mark Evans
          Hi. I m looking for a simple plug-in or extension for ARC VIEW in order to calculate some semivariograms for my forest landscape. ANyone know of any scripts
          Message 4 of 6 , Jul 8, 1999
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            Hi.

            I'm looking for a simple plug-in or extension for ARC VIEW in order
            to calculate some semivariograms for my forest landscape.

            ANyone know of any scripts for download etc ?

            Thanks,

            Mark
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