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GEOSTATS: autologistic versus co-indicator kriging

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  • Wayne Thogmartin
    Modeling a species presence/absence across a landscape is an increasingly common procedure in wildlife research. However, rarely does this research account
    Message 1 of 1 , Nov 9, 1999
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      Modeling a species presence/absence across a landscape is an increasingly
      common procedure in wildlife research. However, rarely does this research
      account for the autocorrelated nature of the data one might collect at,
      say, point counts. I would like to incorporate the spatial dependency of
      this sort of data to improve the output of my modeling efforts.

      My interest is in predicting the historical presence of a species across
      the state of Illinois. I could do this with autologistic regression with
      covariates. However, I could also do this with some sort of indicator
      kriging that incorporates covariates. The covariates in both cases would
      be environmental variables such as patch size, cover type, proximity to
      stream, etc.

      Is anyone aware why one method might be preferable to the other? I have
      not seen any literature on indicator co-kriging though I'm sure it must
      exist. Can anyone point me to relevant literature and to codes or programs
      that would facilitate either procedure?

      Thanks,



      Wayne Thogmartin wthogma@...
      Upland Wildlife/Habitat Project 618.453.5495 (office)
      Mail Code 6504
      Cooperative Wildlife Research Laboratory 618.453.6944 (fax)
      Southern Illinois University
      Carbondale, IL 62901-6504

      http://www.science.siu.edu/zoology/gradstudents/thogmartin/thogmartin.html

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