Bayesian spatial models with a mixture neighborhood structure.

Nenhuma Miniatura disponível
Data
2012
Título da Revista
ISSN da Revista
Título de Volume
Editor
Resumo
In 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.
Descrição
Palavras-chave
Disease mapping, Markov random field, Spatial hierarchical models
Citação
RODRIGUES, 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.