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Autologistic models with interpretable parameters

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Abstract

Ecologists are interested in characterizing succession processes, in particular monitoring the spread of invasive species and their effect on resident species. In situations for which binary response variables representing presence or absence of plants are observed over a spatial lattice, it may be desirable to use a model that accounts for the statistical dependence in the data, as well as the effect of potential covariates. One such model is the autologistic regression model. We show that the typical parameterization of the autologistic model presents difficulties in interpreting model parameters across varying levels of statistical dependence, and propose an alternative (centered) parameterization that overcomes this difficulty.We use the centered autologistic model to study the dynamics over time of two species, Rumex acetosella and Lonicera japonica, in an abandoned agricultural field in New Jersey, and compare the results to those obtained from using the traditional autologistic parameterization.

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Authors and Affiliations

  1. Department of Statistics, Iowa State University, 50011-1210, Ames, IA

    Petruţa C. Caragea (Assistant Professor) & Mark S. Kaiser (Professor)

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  1. Petruţa C. Caragea
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  2. Mark S. Kaiser
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Correspondence to Petruţa C. Caragea.

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Caragea, P.C., Kaiser, M.S. Autologistic models with interpretable parameters. JABES 14, 281–300 (2009). https://doi.org/10.1198/jabes.2009.07032

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  • DOI: https://doi.org/10.1198/jabes.2009.07032

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