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Environmental and Ecological Statistics

, Volume 4, Issue 1, pp 31–48 | Cite as

Modelling the distribution of plant species using the autologistic regression model

  • Hulin Wu
  • F Red W. Huffer
Article

Abstract

For modeling the distribution of plant species in terms of climate covariates, we consider an autologistic regression model for spatial binary data on a regularly spaced lattice. This model belongs to the class of autologistic models introduced by Besag (1974). Three estimation methods, the coding method, maximum pseudolikelihood method and Markov chain Monte Carlo method are studied and comparedvia simulation and real data examples. As examples, we use the proposed methodology to model the distributions of two plant species in the state of Florida.

binary data coding method ecological data environmental statistics Markov chain Monte Carlo plant species pseudolikelihood spatial data 

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Copyright information

© Chapman and Hall 1997

Authors and Affiliations

  • Hulin Wu
    • 1
  • F Red W. Huffer
    • 2
  1. 1.Frontier Science & Technology Research Foundation, Inc.BrooklineUSA
  2. 2.Department of StatisticsThe Florida State UniversityTallahasseeUSA

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