Rodrigues, Erica CastilhoAssunção, Renato Martins2015-04-132015-04-132012RODRIGUES, E. C.; ASSUNÇÃO, R. M. Bayesian spatial models with a mixture neighborhood structure. Journal of Multivariate Analysis, v. 109, p. 88-102, 2012. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0047259X12000589>. Acesso em: 13 abr. 2015.0047-259Xhttp://www.repositorio.ufop.br/handle/123456789/5043In Bayesian disease mapping, one needs to specify a neighborhood structure to make inference about the underlying geographical relative risks. We propose a model in which the neighborhood structure is part of the parameter space. We retain the Markov property of the typical Bayesian spatial models: given the neighborhood graph, disease rates follow a conditional autoregressive model. However, the neighborhood graph itself is a parameter that also needs to be estimated. We investigate the theoretical properties of our model. In particular, we investigate carefully the prior and posterior covariance matrix induced by this random neighborhood structure, providing interpretation for each element of these matrices.en-USDisease mappingMarkov random fieldSpatial hierarchical modelsArtigo publicado em periodicoO periódico Journal of Multivariate Analysis concede permissão para depósito do artigo no Repositório Institucional da UFOP. Número da licença: 3603161455883.https://doi.org/10.1016/j.jmva.2012.02.017