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AI-GEOSTATS: spatial statistics for small data sets

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  • Raechel Waters
    Dear All, I am new to spatial statistics and am posting this query in the hope that someone may be able to point me in the right direction. I am a biological
    Message 1 of 2 , Jan 22, 2001
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      Dear All,

      I am new to spatial statistics and am posting this query in the hope that
      someone may be able to point me in the right direction. I am a biological
      oceanographer and am interested in statistically describing the
      2-dimensional distribution of biological particles, primarily to define the
      'patchiness' of the distributions. I have two data sets which consist of
      7x7 and 9x9 point arrays, providing 49 and 81 samples respectively. Are
      there meaningful spatial statistics that can be applied to such small data
      sets?

      Thank you in advance,

      Raechel Waters

      `````````````````````````````````````````````````````
      Marine Biology
      School of Biology
      Flinders University
      GPO Box 2100
      Adelaide
      SA 5001

      Phone: 08 8201 5234
      Fax: 08 8201 3015
      Mobile: 0401 304 106


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    • Isobel Clark
      Dear Raechel The answer to your question is a bit chicken-and-egg-ish. If your data is well behaved (simple distribution, pretty continuous) then you can get
      Message 2 of 2 , Jan 23, 2001
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        Dear Raechel

        The answer to your question is a bit
        chicken-and-egg-ish.

        If your data is well behaved (simple distribution,
        pretty continuous) then you can get meaningful results
        from very few samples (probably not less than 20 or
        so!!)

        We have examples in the book with data sets of 27 and
        up. The 27 one is no good for geostatistics but this
        has more to do with the fact that the samples are 1km
        apart when the range of influence is probably about
        125 metres. The main tutorial set in the old book
        (available free at
        http://uk.geocities.com/drisobelclark/practica.html)
        which we now call "Page 95" has 50 samples very
        inefficiently placed which still yield good results
        for interpretation and estimation purposes. Even more
        so for simulation basis.

        So, I would say, go ahead and try it but look at your
        distribution before you go to geostatistics. Small
        data sets will give much better results if Normal
        (Gaussian) or normalised or transformed in some other
        way.

        If I can be of any more help, please let me know
        Isobel Clark



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