Loading ...
Sorry, an error occurred while loading the content.

Re: AI-GEOSTATS: spatial GLMM with nested correlation structure

Expand Messages
  • Edzer J. Pebesma
    John, the gstat R package/S-Plus library, found at http://www.gstat.org/s.html does provide nested variograms, each having their own anisotropy parameters.
    Message 1 of 4 , Feb 5, 2004
    • 0 Attachment
      John, the gstat R package/S-Plus library, found at

      http://www.gstat.org/s.html

      does provide nested variograms, each having their
      own anisotropy parameters. However, it does not
      do a fully integrated variogram parameter estimation
      in a Poisson framework; you'd have to work with
      residuals. More specificly, it does not fit anisotropy
      ratios nor directions; only sills and ranges.
      --
      Edzer

      John Jansen wrote:

      >Hello all -- I'm in the midst of modeling the distribution of
      >ice-hauling seals in relation to covariates such as day of year (DOY)
      >and ice cover (ICE.COV). By strip-transect sampling on 20 separate
      >days, I have created a lattice of cells containing seal counts and the
      >corresponding covariate measures. To remove a significant north-south
      >trend in seal counts, I extracted the residuals from a GAM loess smooth
      >of seal counts on the lat/long variables. Modeling the residuals, I
      >arrived at the following S+ best fit (using AIC):
      >
      >glmmPQL(sealsum.gamfit ~ ICE.COV * DOY * SHIPACT2, random = ~ 1| DOY,
      >family = poisson, data = yakgrid.fit, correlation = corGaus(form = ~
      >lat.yak + lon.yak | DOY), verbose = T))
      >
      >I determined that a gaussian variogram best fit the spatial
      >autocorrelation by exploring the data in Surfer, VarioWin, and S+. But
      >I have encountered a significant degree of both geometric and zonal
      >anisotropy. I believe the anisotropy is real as there are several
      >reasonable hypothesis that explain its presence which have to do with
      >the seals concentrating in a stream of ice, i.e., creating
      >discontinuities in variance and correlation within the study area.
      >Though complicated, I have been able to model the autocorrelation (in
      >VarioWin) by nesting two spatial structures (both Gaussian)
      >corresponding to the directions of maximum and minimum continuity. The
      >problem is that I now need to transport this nested model into the S+
      >spatial GLMM framework. The avenues I have explored thus far are:
      >
      >1) create a new corStruct class in S+ that corresponds to a
      >gaussian-gaussian nested model. Problem: I have been unable to find
      >any documentation on how to create a new class though the online help
      >indicates that it is possible "by specifying a constructor function and
      >methods for the functions corMatrix and coef".
      >
      >2) transforming/weighting the coordinates prior to running the model.
      >Problem: though a geometric transform of the coordinates is
      >straightforward it is less obvious how to conduct such a transform using
      >a nested model.
      >
      >It may be I'm forcing a square peg (nested model) in a round hole (S+
      >spatial GLMM), but I'm hoping someone out there has done this in S+
      >before and can pass along their experience. Otherwise, I'm soliciting
      >the wisdom of those who know where to find the square hole that matches
      >my square peg, i.e., other software or techniques that allow one to
      >account for spatial correlation with nested structures with the main
      >focus of modeling the relation of animals to their environment. Much
      >gratitude to any assistance. Thanks, John Jansen
      >
      >
      >--
      >John K. Jansen
      >Wildlife Biologist
      >National Marine Mammal Laboratory
      >NOAA Fisheries
      >7600 Sand Point Way N.E. Bldg 4
      >Seattle, WA 98115-6349
      >voice: 206.526.4027
      >fax: 206.526.6615
      >email: John.Jansen@...
      >
      >
      >
      >--
      >* To post a message to the list, send it to ai-geostats@...
      >* As a general service to the users, please remember to post a summary of any useful responses to your questions.
      >* To unsubscribe, send an email to majordomo@... with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list
      >* Support to the list is provided at http://www.ai-geostats.org
      >
      >


      --
      * To post a message to the list, send it to ai-geostats@...
      * As a general service to the users, please remember to post a summary of any useful responses to your questions.
      * To unsubscribe, send an email to majordomo@... with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list
      * Support to the list is provided at http://www.ai-geostats.org
    Your message has been successfully submitted and would be delivered to recipients shortly.