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Re: AI-GEOSTATS: Multinomial (Discrete) Kriging

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  • Brian R Gray
    are you working with nominal or ordinal data? if you are interested in inferences on the mean and if spatial correlation isn t exceptional, then you can lump
    Message 1 of 2 , Nov 29, 2001
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      are you working with nominal or ordinal data? if you are interested in
      inferences on the mean and if spatial correlation isn't exceptional, then
      you can lump correlation with other sources of overdispersion and use an
      overdispersion estimate to adjust the expected variance (ie
      psi*pi(1-pi)/n). since you're interested in the correlation itself you may
      be in a different world. within a modeling context, multinomial analysis
      often assumes an underlying or latent distribution (distributions plural
      under some assumptions). Chiles and Delfiner (pp100-103) demonstrate how
      the correlation associated with a latent bivariate Gaussian is more or less
      retained when dichotomized near the mean but is rapidly lost as the
      dichotomization moves away from the latent mean. I would imagine (but
      don't know) that--using the median and shape--similar arguments could be
      made for other latent distributions. this would appear to suggest that you
      may expect correlation to be highest for nominal or cumulative categories
      with prevalence nearest .5. if your data are not at least 1st-order
      stationary, then you may expect both the categories nearest the median and
      the correlation of all categories to change over space. I would appreciate
      other comments on this topic. brian

      ***************************************************************
      Brian Gray
      USGS Upper Midwest Environmental Sciences Center
      575 Lester Road
      Onalaska, WI 54650
      608-783-7550 ext 19
      FAX 608-783-8058
      brgray@...
      ****************************************************************



      Kenneth Cabrera
      <krcabrer@... To: "ai-geostats@..." <ai-geostats@...>
      ed.edu.co> cc:
      Sent by: Subject: AI-GEOSTATS: Multinomial (Discrete) Kriging
      ai-geostats-list@unil.c
      h


      11/29/2001 08:27 AM
      Please respond to
      Kenneth Cabrera





      Hi list!

      I want to know if there any software that works with multinomial
      (discrete) spatial variable.

      Is it valid to work pairwaise with binomial variable and make a join
      to obtain the multinomial distribution?

      Thank you very much for your help

      Kenneth


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