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1089AI-GEOSTATS: Declustering

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  • Michael Pyrcz
    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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