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Re: AI-GEOSTATS: Choosing Lag Distance and Angular Tolerance

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  • Isobel Clark
    Andrew You can apply standard geostatistics if the measurements are the average (or some similar feature) over an area. It makes interpeting the
    Message 1 of 5 , May 15, 2001
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      Andrew

      You can apply 'standard' geostatistics if the
      measurements are the 'average' (or some similar
      feature) over an area.

      It makes interpeting the semi-variogram extremely
      tricky if you combine many different sizes of sample,
      but common sense is the main thing here. The trick is
      to derive a point semi-variogram model from which any
      size can be derived (see Chapter 3, Practical
      Geostatistics 1979, downloadable free from Web,
      http://uk.geocities.com/drisobelclark/practica.html)

      Kriging is modified to reflect that the samples are
      averages, mainly by changing the diagonal elements in
      the equations so that they are non-zero. I don't know
      any software package (off hand ) that does this,
      though.

      Isobel Clark



      --- Andrew Mullens <andrew_mullens@...>
      wrote: > I have a question relating to this question,
      > certainly not to question the
      > previous writer, it just seems like a good time to
      > bring it up. Will
      > variograming and other such techniques work for the
      > data the previous writer
      > described, e.g samples aren't at points, but areas
      > (and areas that might
      > have very little to do with the question). If they
      > did use points in the
      > calculations where would the points be placed, at
      > the center of the county,
      > at the major population center, at some arbitrary
      > point (e.g most northerly
      > point).
      >
      > I may be miss reading the description, perhaps the
      > sample are point samples,
      > but were taken with one sample in each county.
      >
      > Obviously the point samples are never really point
      > sample, they must be
      > taken over some area, approximating a point, but
      > does this design seem to
      > push the boundaries on that assumption.
      >
      > Andrew
      > ----- Original Message -----
      > From: "Yadollah Waghei" <waghei@...>
      > To: <ai-geostats@...>
      > Cc: <waghei_y.MED.TMU@...>;
      > <mohsen_m@...>; <waghei@...>;
      > <mohsen_m@...>; <kazem_an@...>;
      > <Faghihzadeh@...>
      > Sent: Tuesday, May 15, 2001 7:33 AM
      > Subject: AI-GEOSTATS: Choosing Lag Distance and
      > Angular Tolerance
      >
      >
      > > Hello dears
      > > I have a spatial data set contaning n=262
      > observarion (The variable of
      > interest is Rate of Tuberculosis in 262 counties of
      > Iran). I want to fit
      > some models to Directional semi-variograms,and then
      > build anisotropic
      > semi-variogram.
      > > Then questions are
      > > - Is there any rule for choosing Lag Distance and
      > Angular Tolerance?
      > > -Also,how we can balance between Lag Distance and
      > Angular Tolerance?
      > > -Do you agree that both must be very small,as
      > possible?(Such that number
      > of pairs in each lag>20, for example)
      > >
      > > Thank you
      > > Yadollah Waghei
      > > Dep.of Biostatistics
      > > Tarbiat Modarres Univ.(Tehran)Po.Box: 14115-111
      > > Tel:8011001-3872 Fax:8007989
      > >
      >
      ___________________________________________________________________________
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      > web-based communications
      > center.
      > > Visto.com. Life on the Dot.
      > >
      > >
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    • Isobel Clark
      ... wrote: ... This is something I learned about in quantitative ecology in the 1960 s ;-) You take each sample in turn and find the sample closest to it.
      Message 2 of 5 , May 15, 2001
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        --- Lucie Vallée <Lucie_Vallee@...>
        wrote: >
        >
        > Could you explain what you mean by "nearest
        > neighbour distances between samples locations"?
        This is something I learned about in quantitative
        ecology in the 1960's ;-)

        You take each sample in turn and find the sample
        closest to it. Note the distance. A histogram of the
        distances will give you a sort of natural inter-sample
        distance for use in the semi-variogram calculation.

        The histogram can also be used to check whether
        sampling is randon, uniform, clustered etc.

        I don't have a full reference but it should be easy to
        find: Pielou, Cressie or any other book with Spatial
        Statistics in the title.

        Isobel Clark


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