Autologistic models with interpretable parameters

Journal of Agricultural, Biological, and Environmental Statistics

Volumn 14, Issue 3, 2009, Pages 281-300

  Caragea, Petruţa C ^a   Kaiser, Mark S ^a  

^a Department of Statistics Center for Statistics and Applications in Forensic Evidence Iowa State University 2438 Osborn Dr Ames   (United States)

Author keywords

Binary response; Conditionally specified models; Large scale; Old field succession; Parameter interpretation; Smallscale model structure; Spatial models

Indexed keywords

AGRICULTURAL LAND; ANGIOSPERM; ECOLOGICAL MODELING; ECOSYSTEM RESPONSE; INVASIVE SPECIES; NUMERICAL MODEL; PARAMETERIZATION; REGRESSION ANALYSIS; STATISTICAL DATA; SUCCESSION;

NEW JERSEY; UNITED STATES;

LONICERA JAPONICA; RUMEX; RUMEX ACETOSELLA;

EID: 77951710151     PISSN: 10857117     EISSN: 15372693     Source Type: Journal    
DOI: 10.1198/jabes.2009.07032     Document Type: Article

References (17)

1. Barden, L. S., and Matthews, J. F. (1980), "Change in Abundance of Honeysuckle (Lonicera japonica) and Other Ground Flora After Prescribed Burning of a Piedmont Pine Forest," Castanea, 45, 257-260.
2. Besag, J. (1974), "Spatial Interaction and the Statistical Analysis of Lattice Systems" (with discussion), Journal of the Royal Statistical Society, Ser. B, 36, 192-236.
3. Besag, J. (1975), "Statistical Analysis of Non-Lattice Data," The Statistician, 24, 179-195.
4. Buell, M. F., Buell, H. F., Small, J. A., and Siccama, T. G. (1971), "Invasion of Trees in Secondary Succession on the New Jersey Piedmont," Bulletin of the Torrey Botanical Club, 98, 67-74.
5. Cressie, N. (1993), Statistics for Spatial Data (2nd ed.), New York: Wiley.
6. Dormann, F. C., McPherson, J. M., Araújo, M. B., Bivand, R., Bolliger, J., Carl, G., Davies, R. G., Hirzel, A., Jetz, W., Kissling, W. D., Kühn, I., Ohlemüller, R., Peres-Neto, P. R., Reineking, B., Schröder, B., Schurr, F. M., and Wilson, R. (2007), "Methods to Account for Spatial Autocorrelation in the Analysis of Species Distributional Data: A Review," Ecography, 30 (5), 609-628.
7. Gelman, A., and Meng, X. L. (1998), "Simulating Normalizing Constants: From Importance Sampling to Bridge Sampling and Path Sampling," Statistical Science, 13, 163-185.
8. Geyer, C. J., and Thompson, E. A. (1992), "Constrained Monte-Carlo Maximum Likelihood for Dependent Data" (with discussion), Journal of the Royal Statistical Society, Ser. B, 54, 657-699.
9. Gumpertz, M. L., Graham, M. J., and Ristaino, J. B. (1997), "Autologistic Model of Spatial Pattern of Phytophtora Epidemic in Bell Pepper: Effects of Soil Variables on Disease Presence," Journal of Agricultural, Biological, and Environmental Statistics, 2, 131-156.
10. Guyon, X. (1995), Random Fields on a Network: Modeling, Statistics, and Applications, New York: Springer.
11. Hoeting, J. A., Leecaster, M., and Bowden, D. (2000), "An Improved Model for Spatially Correlated Binary Responses," Journal of Agricultural, Biological, and Environmental Statistics, 5, 102-114.
12. Kaiser, M. S., Daniels, M. J., Furukawa, K., and Dixon, P. (2002), "Analysis of Particulate Matter Air Pollution Using Markov Random Field Models of Spatial Dependence," Environmetrics, 13, 615-628.
13. Myster, R. W., and Pickett, S. T. A. (1994), "A Comparison of Rate of Succession Over 18 Years in 10 Contrasting Old Fields," Ecology, 75 (2), 387-392.
14. Pickett, S. T. A. (1982), "Population Patterns Through Twenty Years of Oldfield Succession," Vegetatio, 49, 45-59.
15. Wu, H., and Huffer, F. W. (1997), "Modeling the Distribution of Plant Species Using the Autologistic Regression Model," Environmental and Ecological Statistics, 4, 49-64.
16. Yurkonis, K. A., Meiners, S. J., and Wachholder, B. E. (2005), "Invasion Impacts Diversity Through Altered Community Dynamics," Journal of Ecology, 93, 1053-1061.
17. Zhu, J., Huang, H.-C., and Wu, J. (2005), "Modeling Spatial-Temporal Binary Data Using Markov Random Fields," Journal of Agricultural, Biological, and Enviromental Statistics, 10, 212-225.