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1860P.S. Re: [ai-geostats] Regression vs. Kriging vs. Simulation vs. IDW

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  • Gali Sirkis
    Jan 3, 2005
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      When comparing kriging versus regression, I meant
      using linear regression between sparse and exhaustive
      datasets to interpolate the sparse one, since as Digbi
      Milligan pointed out in general case regression is not
      an estimation method.

      --- Gali Sirkis <donq20vek@...> wrote:

      > Seumas,
      >
      > see few practical points that you may find useful:
      >
      > 1. kriging vs regression:
      >
      > a) kriging honors original data points, while
      > regression does not
      > b) kriging allows to account for anizotropy
      > c) kriging allows to control the influence of the
      > data
      > points
      >
      > 2. Kriging versus other interpolation technics
      >
      > a) Kriging allows to decluster data
      > b) kriging allows to estimate uncertainty of
      > estimation
      > c) kriging allows to use for estimation secondary
      > information from another exhaustive dataset
      >
      > 3. Kriging vs simulations
      >
      > a) Kriging produces smoother version than real
      > distribution, while simulation gives more details
      > b) simulations allow to estimate joint uncertainty,
      > for example probability that values in several
      > adjacent points are above certain level.
      > c) simulation allows to estimate risk of various
      > scenarios - while kriging only shows the most
      > probable
      > one.
      >
      > All the best,
      >
      > Gali Sirkis.
      >
      >
      > >
      > > Hello everyone,
      > >
      > > I apologize if this question is too elementary for
      > > this list;
      > > I want to understand the key differences between
      > > linear regression,
      > > kriging, conditional simulation and other
      > > interpolation techniques such as
      > > IDW or splines in the analyses of spatial data. I
      > > would like to know the
      > > assumptions, strengths and weaknesses of each
      > > method, and when one method
      > > should be preferred to another. I browsed the
      > > archives and looked at some
      > > of the on-line papers, but they are written at a
      > > level beyond my own
      > > current understanding. It seems to me that this
      > > would be a great topic for
      > > the first chapter of an introductory spatial
      > > analysis textbook. Can anyone
      > > recommend any basic textbooks or references on
      > this
      > > topic?
      > > Any assistance you can offer would be appreciated.
      > >
      > > Sincerely,
      > >
      > > Seumas Rogan
      > >
      > >
      > >
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