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

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  • Andrew Mullens
    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
    Message 1 of 5 , May 15, 2001
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      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
      >
      ___________________________________________________________________________
      > Visit http://www.visto.com/info, your free web-based communications
      center.
      > Visto.com. Life on the Dot.
      >
      >
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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 2 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
        > >
        >
        ___________________________________________________________________________
        > > Visit http://www.visto.com/info, your free
        > web-based communications
        > center.
        > > Visto.com. Life on the Dot.
        > >
        > >
        > > --
        > > * To post a message to the list, send it to
        > ai-geostats@...
        > > * As a general service to the users, please
        > remember to post a summary of
        > any useful responses to your questions.
        > > * To unsubscribe, send an email to
        > majordomo@... with no subject and
        > "unsubscribe ai-geostats" followed by "end" on the
        > next line in the message
        > body. DO NOT SEND Subscribe/Unsubscribe requests to
        > the list
        > > * Support to the list is provided at
        > http://www.ai-geostats.org
        > >
        >
        >
        > --
        > * To post a message to the list, send it to
        > ai-geostats@...
        > * As a general service to the users, please remember
        > to post a summary of any useful responses to your
        > questions.
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        > the list
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        http://www.ai-geostats.org


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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 3 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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