Modelling the distribution of plant species using the autologistic regression model |
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Authors: | Wu Hulin Huffer F Red W |
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Institution: | (1) Frontier Science & Technology Research Foundation, Inc., 303 Bolyston Street, Brookline, MA 02146, USA;(2) Department of Statistics, The Florida State University, Tallahassee, FL 32306, USA |
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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. |
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Keywords: | binary data coding method ecological data environmental statistics Markov chain Monte Carlo plant species pseudolikelihood spatial data |
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