Bayesian spatial models with a mixture neighborhood structure.

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorRodrigues, Erica Castilho-
Autor(es): dc.creatorAssunção, Renato Martins-
Data de aceite: dc.date.accessioned2025-08-21T15:13:36Z-
Data de disponibilização: dc.date.available2025-08-21T15:13:36Z-
Data de envio: dc.date.issued2015-04-13-
Data de envio: dc.date.issued2015-04-13-
Data de envio: dc.date.issued2012-
Fonte completa do material: dc.identifierhttp://www.repositorio.ufop.br/handle/123456789/5043-
Fonte completa do material: dc.identifierhttps://doi.org/10.1016/j.jmva.2012.02.017-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1006949-
Descrição: dc.descriptionIn 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.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Direitos: dc.rightsO periódico Journal of Multivariate Analysis concede permissão para depósito do artigo no Repositório Institucional da UFOP. Número da licença: 3603161455883.-
Palavras-chave: dc.subjectDisease mapping-
Palavras-chave: dc.subjectMarkov random field-
Palavras-chave: dc.subjectSpatial hierarchical models-
Título: dc.titleBayesian spatial models with a mixture neighborhood structure.-
Aparece nas coleções:Repositório Institucional - UFOP

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