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GEOSTATS: cdf and ccdf

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  • Ulrich Leopold
    Dear all, I have some questions on the difference between the cumulative distribution function (cdf) and the conditional cumulative distribution function
    Message 1 of 1 , May 18, 1999
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      Dear all,

      I have some questions on the difference between the cumulative
      distribution function (cdf) and the conditional cumulative
      distribution function (ccdf).

      I am not sure when I do infer the cdf and when do I infer the
      ccdf by using various geostatistical tools.

      If I want to infer the cdf of my continous variable Z at location u
      (Z(u)) I have to calculate the sample histogram of all samples z(u_n,
      n=1,...,n). Then I can determine the cdf-mean (expected value) which
      is the sample mean (possibly the declustered mean)? And the a priori
      covariance/variance is my cdf-covariance/variance?

      When I use kriging I get the ccdf-mean (?) as an least squared error
      estimate which is my kriging estimate z*(u) (using the neighbouring
      sample values z(u_n)). The ccdf-covariance (?) is inferred through
      the covariance/variogram model that is specified before.

      In contrast, indicator kriging provides the whole ccdf (?) at an
      unsampled location u inferred through the kriging of the transformed
      sample values around.

      So in both approaches
      1) I use the neighbouring data (to infer the ccdf)?
      2) in the first case I only infer the first two moments of the
      ccdf (mean, covariance), in the indicator approach the whole ccdf is
      inferred?

      I would be grateful for any comments to see if I am on the right or
      on the wrong way.

      Thanks so far.

      Ulrich

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

      Ulrich Leopold

      Department of Soil Science
      The University of Trier

      E-mail: leop6101@...
      phone: 0049-(0)651-140764
      address: Engelstr.104, 54292 Trier, Germany
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