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Re: AI-GEOSTATS: I'm new

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  • Koen Hufkens
    ... I never used variowin but it seems quite nice, and more important free! Here is a introduction to variowin:
    Message 1 of 5 , Mar 31, 2004
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      > 3) Software. All software for geostatistics have a similar architecture.
      > Try Geoeas & Variowin (free) until you become confident with words like
      > semivariogram, covariance, kriging, block kriging. There if
      > unfortunately no manual for Variowin. I will ask Yvan Pannatier (the
      > author of Variowin) if there is any way to get an electronic copy of his
      > book (out of print since a few years) or of the help file that I can put
      > on the ai-geostats web site. There is nothing else available now and it
      > is much needed. I think this is the best way to have an idea on what the
      > whole is about. The software mentioned above can be downloaded for free
      > and there are plenty of other tools for more advanced geostatistics.

      I never used variowin but it seems quite nice, and more important free!

      Here is a introduction to variowin:

      http://sal.agecon.uiuc.edu/csiss/pdf/variowin.pdf

      There should be more on the net if you look for it, I think...

      If you need automatisation of certain procedures look into R and the
      following packages:

      -spatstat
      -geoR
      -sgeostat
      -spdep
      -gstat (can also be used as stand alone program)

      All this software is open sourced and freely available!

      It made my repetitive work very easy.

      Best regards,
      Koen

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    • Pierre Goovaerts
      Hi Mark, For each number of samples you wish to eliminate, you really need to repeat the sampling many times in order to account for sampling fluctuations in
      Message 2 of 5 , Mar 31, 2004
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        Hi Mark,

        For each number of samples you wish to eliminate,
        you really need to repeat the sampling many times in order
        to account for sampling fluctuations in the assessment
        of prediction performances.
        The procedure need to be automated and you won't avoid
        having to modify a program (i.e. Gslib kt3d whose source code
        is distributed freely) to implement the hundreds or thousands of
        run needed for a thorough analysis. Just as an illustration
        of the kind of fluctuations you can expect if you select
        randomly 100 subsets of the same size, look at the following
        paper that can be downloaded from my webpage:

        Saito, H. and P. Goovaerts. 2000. Geostatistical interpolation of
        positively skewed and censored data in a dioxin contaminated site.
        Environmental Science & Technology, vol.34, No.19: 4228-4235.

        Regards,

        Pierre

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

        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 Wed, 31 Mar 2004, Mark Dowdall wrote:

        >
        >
        > Hello
        >
        > This is a newbie question but I have been all over the Faqs and cannot
        > find an answer.
        >
        > Any help is appreciated and a summary of answers will be posted.
        >
        > I have a set of data that was taken over a particular area. I have
        > kriged and contoured and am happy with the results.
        >
        > But I need to demonstrate, within the bounds of the
        > study/analysis/assumptions, that the number of samples taken was
        > sufficient to describe the area.
        >
        > So my plan was to demonstrate that for a cetain number of samples the
        > variance in the estimates had reached a value that could not be reduced
        > efefctively by increasing sample number.
        >
        > And I thought this could be done by eliminating at random a point (so I
        > have x-1 data points), kriging the remainder with the chosen parameters
        > and checking the relevant parameters. (x is the number of actual
        > samples)
        >
        > Then eliminating two points at random (x-2), repeating and so on.
        > Eventually only 1 point being left.
        >
        > But.....if I eliminate the first point at random, does it matter which
        > point is eliminated? Or in the first instance (x-1 points) should I do
        > the process for all possible samples and take an average of the
        > estimation uncertainty?
        >
        > I am using GEOEAS and this could take a long time as all possible
        > permutations of for example x-20 could be quite large.
        >
        > I did download Explostat which has a feature that sems to do this
        > automatically but the manual is not great and the software is a little
        > impenetrable.
        >
        > If anyone can shed light on this I would be most grateful.
        >
        > Thanks in advance
        >
        > M.dowdall
        >
        > Ie.
        >
        >
        >
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        >

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