Spatial latent class analysis model for spatially distributed multivariate binary data

Alvarez, R.M., Nagler, J., 2001. Correlated disturbances in discrete choice models: A comparison of multinomial probit and logit models. Working Paper at California Institute of Technology, Division of the Humanities and Social Sciences Bandeen-Roche, 1997, Latent variable regression for multiple discrete outcomes, Journal of the American Statistical Association, 92, 1375, 10.2307/2965407 Beron, 2004, Probit in a spatial context: A Monte Carlo analysis, 169 Besag, 1974, Spatial interaction and the statistical analysis of lattice systems, Journal of the Royal Statistical Society, Series B, 23, 192 Bolduc, 1992, Generalized autoregressive errors in the multinomial probit model, Transportation Research B, 26, 155, 10.1016/0191-2615(92)90005-H Bolduc, 1999, A practical technique to estimate multinomial probit models in transportation, Transportation Research B, 33, 63, 10.1016/S0191-2615(98)00028-9 Bolduc, 1997, Multinomial probit estimation of spatially interdependent choices: An empirical comparison of two new techniques, International Regional Science Review, 20, 77, 10.1177/016001769702000105 Bunch, 1991, Estimability in the multinomial probit model, Transportation Research B, 25, 1, 10.1016/0191-2615(91)90009-8 Carlin, 2008 Celeux, 2006, Deviance information criteria for missing data models, Bayesian Analysis, 4, 651, 10.1214/06-BA122 Cheng, 2007, Testing for IIA in the multinomial logit model, Sociological Methods and Research, 35, 583, 10.1177/0049124106292361 Clogg, 1984, Latent structure analysis of a set of multidimensional contingency tables, Journal of the American Statistical Association, 79, 762, 10.2307/2288706 Daganzo, 1979 Dey, 1995, A Bayesian predictive approach to determining the number of components in a mixture distribution, Statistics and Computing, 5, 297, 10.1007/BF00162502 Diggle, 1998, Model-based geostatistics (with discussion), Applied Statistics, 47, 299 Gelfand, 2003, Proper multivariate conditional autoregressive models for spatial data analysis, Biostatistics, 4, 11, 10.1093/biostatistics/4.1.11 Green, 1995, Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrika, 82, 711, 10.1093/biomet/82.4.711 Grzebyk, 1994, Multivariate analysis and spatial/temporal scales: real and complex models, 19 Holloway, 2002, Bayesian spatial probit estimation: A primer and an application to HYV rice adoption, Agricultural Economics, 27, 383, 10.1111/j.1574-0862.2002.tb00127.x Jin, 2005, Generalized hierarchical multivariate CAR models for areal data, Biometrics, 61, 950, 10.1111/j.1541-0420.2005.00359.x Komac, M., Sajn, R., 2001. Polluted or nonpolluted—A fuzzy approach determining soil pollution. In: Proceeding of the Annual Conference of the International Association for Mathematical Geology Lacy, 1999, The vote-stealing and turnout effects of Ross Perot in the 1992 US presidential election, American Journal of Political Science, 43, 233, 10.2307/2991792 Mardia, 1993, Spatial-temporal analysis of multivariate environmental monitoring data, 347 McCutcheon, 1987 McFadden, 1981, An application of diagnostic tests for the independence from irrelevant alternatives property of the multinomial logit model, Transportation Research Board Record, 637, 39 McMillen, 1992, Probit with spatial autocorrelation, Journal of Regional Science, 32, 335, 10.1111/j.1467-9787.1992.tb00190.x Mohammadian, A., Haider, M., Kanaroglou, P., 2005. Incorporating observed spatial dependencies in random parameter discrete choice models. In: Proceedings of the 84th Annual Meeting of the Transportation Research Board, Washington DC Muthen, 1998 Reboussin, 1999, Estimating equations for a latent transition model with multiple discrete indicators, Biometrics, 55, 839, 10.1111/j.0006-341X.1999.00839.x Schmidheiny, K., 2003. Income segregation and local progressive taxation: Empirical evidence from Switzerland. Working Paper, Diskussionsschriften dp0311, Universitaet Bern, Departement Volkswirtschaft Smith, 2004, A Bayesian probit model with spatial dependencies Spiegelhalter, 2002, Bayesian measures of model complexity and fit (with discussion), J. Roy. Statist. Soc., Ser. B, 64, 583, 10.1111/1467-9868.00353 Spiegelhalter, D.J., Thomas, A., Best, N., Lunn, D., 2004. Winbugs version 1.4.1 manual. http://www.mrc-bsu.cam.ac.uk/bugs Wackernagel, 2003