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AI-GEOSTATS: 3D ranges in GSLIB

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  • Maria N. Morales
    Dear list, I am kriging in 3D using GSLIB library. In p. 27-28 of its user s guide, the rotation angles are defined, as ang1, ang2 and ang3. This angles refer
    Message 1 of 3 , Feb 10, 2004
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      Dear list,

      I am kriging in 3D using GSLIB library.

      In p. 27-28 of its user's guide, the rotation angles are defined, as ang1, ang2 and ang3.
      This angles refer to:
      ang1: rotation over z axis to find anisotropy's elipsoid azimut
      ang2: rotation over x axis to find anisotropy's elipsoid dip
      ang3: rotation over y axis to find anisotropy's elipsoid plunge

      The elipsoid defines 3 axes with ranges maximum, intermediate and minimum.
      The maximum one is located in direction defined by ang1 and ang 2.
      The other two axes, are in perpendicular plane to the direction of the maximum.

      I would like to know if the definition of ranges a_hmax, a_hmin, and a_vert are these ranges in actual size or if they are the projection in the horizontal and vertical plane.

      Thank you very much, and hoping to receiving answers from you soon!!

      Maria Morales

      Federal University of Rio Grande do Sul
      Laboratory of Mineral Research
      Porto Alegre
      Brazil


      [Non-text portions of this message have been removed]
    • Monica Palaseanu-Lovejoy
      Hi everyone, I would appreciate any light in defining and separating Monte Carlo resampling techniques and bootstrapping techniques. In my search it seems that
      Message 2 of 3 , Feb 12, 2004
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        Hi everyone,

        I would appreciate any light in defining and separating Monte Carlo
        resampling techniques and bootstrapping techniques. In my search
        it seems that the two notions are more or less the same .... which
        puzzles me - i suppose if there are 2 different names, would be 2
        different definitions - but maybe i am wrong.

        Also, i am interested in calculating prediction intervals for kriging.
        Any reference will be much appreciated. until now i have read only
        "the bootstrap and kriging prediction intervals" by Sara Sjostedt-De
        Luna and Alastair Young, published in 2003 in Scandinavian
        Journal of Statistics.

        If you know about any software which would calculate the kriging
        prediction intervals - would be super.

        Thank you in advance for any help,

        Monica

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      • Ruben Roa Ureta
        ... In bootstrapping you create samples which have not been observed directly from samples which have been observed, while in Monte Carlo you create samples
        Message 3 of 3 , Feb 12, 2004
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          > Hi everyone,
          >
          > I would appreciate any light in defining and separating Monte Carlo
          > resampling techniques and bootstrapping techniques. In my search
          > it seems that the two notions are more or less the same .... which
          > puzzles me - i suppose if there are 2 different names, would be 2
          > different definitions - but maybe i am wrong.

          In bootstrapping you create samples which have not been observed directly
          from samples which have been observed, while in Monte Carlo you create
          samples which have not been observed indirectly from a model for samples
          which have been observed. In bootstrap an observed sample is turned into a
          finite population from which to re-sample, while in Monte Carlo a model
          derived from an observed sample is used to produce an infinite set of
          populations from which to re-sample.
          There are 3 major resampling techniques: bootstrap, Monte Carlo, and
          randomization (aka permutation tests). In the latter, you create samples
          which have not been observed by swapping the indices for the data in
          samples which have been observed instead of creating entirely new data.
          One problematic question which is made transparent by resampling
          techniques, but which also applies to most of statistical inference, is:
          would you base your inference on data which have not been observed?
          R.

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