Modelling the distribution of plant species using the autologistic regression model
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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.
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- Modelling the distribution of plant species using the autologistic regression model
Environmental and Ecological Statistics
Volume 4, Issue 1 , pp 31-48
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers
- Additional Links
- binary data
- coding method
- ecological data
- environmental statistics
- Markov chain Monte Carlo
- plant species
- spatial data