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RE: AI-GEOSTATS: Declustering

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  • Alessandro Gimona
    Isobel wrote: .....The semi-variogram and kriging techniques are not affected by clustering. ... I am slightly confused: ... if sampling is clustered
    Message 1 of 7 , Nov 16, 2001
      Isobel wrote:

      .....The semi-variogram and kriging techniques are not affected by
      clustering.
      > In fact, one of the main reasons for inventing kriging
      > was to make full use of every one of clustered and/or
      > preferentially sited sampling.
      >
      >
      I am slightly confused:
      ... if sampling is clustered preferentially in e.g. higher values
      areas, would this not bias the semi-variogram for the first few lags?...at
      least if, as it can happen, the variance is related to the mean.
      What about the effects of the possible over-estimation of the global
      mean due to clustering?

      thanks

      Alessandro Gimona

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    • oliver.sonnentag@web.de
      hello list, to get the global mean of my data set (484 observation wells) and as a prerequisite for Normal Score Transformation with GSLIB, i declustered my
      Message 2 of 7 , Jul 5, 2003
        hello list,
        to get the global mean of my data set (484 observation wells) and
        as a prerequisite for Normal Score Transformation with GSLIB, i
        declustered my data with polygonal declustering. When
        standardizing the weights to 1, so that the weights sum up to the
        number of data, I receive some negative weights. this results in
        negative values for the observations (nitrate concentration). how do
        i have to interpret this ? does this require a special treatment? skip
        them? as I mentioned before, i want to normal score transform the
        data set prior to simple kriging.
        many many thanx for some help in advance.
        Regards,
        Oliver




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      • Pierre Goovaerts
        Hi Oliver, I don t know which algorithm you are using to compute these declustering weights but there is something wrong in your rescaling procedure. These
        Message 3 of 7 , Jul 5, 2003
          Hi Oliver,

          I don't know which algorithm you are using to compute these declustering
          weights but there is something wrong in your rescaling procedure.
          These declustering weights are proportional to the size of the polygon
          of influence of each observation and they can not be negative.

          Regards,

          Pierre Goovaerts

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

          Dr. Pierre Goovaerts
          President of PGeostat, LLC
          Chief Scientist with Biomedware Inc.
          710 Ridgemont Lane
          Ann Arbor, Michigan, 48103-1535, U.S.A.

          E-mail: goovaert@...
          Phone: (734) 668-9900
          Fax: (734) 668-7788
          http://alumni.engin.umich.edu/~goovaert/

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

          On Sat, 5 Jul 2003 oliver.sonnentag@... wrote:

          > hello list,
          > to get the global mean of my data set (484 observation wells) and
          > as a prerequisite for Normal Score Transformation with GSLIB, i
          > declustered my data with polygonal declustering. When
          > standardizing the weights to 1, so that the weights sum up to the
          > number of data, I receive some negative weights. this results in
          > negative values for the observations (nitrate concentration). how do
          > i have to interpret this ? does this require a special treatment? skip
          > them? as I mentioned before, i want to normal score transform the
          > data set prior to simple kriging.
          > many many thanx for some help in advance.
          > Regards,
          > Oliver
          >
          >
          >
          >
          > --
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          >


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        • Michael Pyrcz
          Good day Oliver, I have another comment on declustering in addition to the previous comment on negative weights. The weights do not actually change the data
          Message 4 of 7 , Jul 5, 2003
            Good day Oliver,

            I have another comment on declustering in addition to the previous
            comment on negative weights. The weights do not actually change the
            data values. They change the weight of the data values within the
            distribution; therefore, weights change the distribution, but not the
            sample data. One way to think of declustering weights is that they
            would change the height on the bars of a histogram (more precisely, the
            contribution of each of the data to the bar height), but not the
            position of the bars.

            The GSLIB book (Deutsch and Journel) has a lot of practical guides to
            declustering. I have recently written a paper on the specifics of
            declustering, if you are interested.

            All the best,

            Michael

            _____________________________________________

            Michael Pyrcz
            Ph.D. Candidate
            Department of Civil & Environmental Engineering
            University of Alberta
            (780) 492-3153
            mpyrcz@...
            www.ualberta.ca/~mpyrcz


            -----Original Message-----
            From: ai-geostats-list@... [mailto:ai-geostats-list@...] On
            Behalf Of oliver.sonnentag@...
            Sent: July 5, 2003 2:13 AM
            To: ai-geostats@...
            Subject: AI-GEOSTATS: Declustering

            hello list,
            to get the global mean of my data set (484 observation wells) and
            as a prerequisite for Normal Score Transformation with GSLIB, i
            declustered my data with polygonal declustering. When
            standardizing the weights to 1, so that the weights sum up to the
            number of data, I receive some negative weights. this results in
            negative values for the observations (nitrate concentration). how do
            i have to interpret this ? does this require a special treatment? skip
            them? as I mentioned before, i want to normal score transform the
            data set prior to simple kriging.
            many many thanx for some help in advance.
            Regards,
            Oliver




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