23º SINAPE - Simpósio Nacional de Probabilidade e Estatística

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Título

EXTENDING JAGS FOR SPATIAL DATA

Data de titulação

22/02/2018

Instituição de titulação

UNIVERSIDADE FEDERAL DE MINAS GERAIS

RESUMO (abstract)

Bayesian hierarchical modeling for spatial data is challenging for professionals from other areas than statistics. From a technical perspective, setting the model and the prior distributions are the simplest part of the process. What makes it difficult is the com- putation of the posterior full conditionals and the implementation of the Gibbs Sampler algorithm. The BUGS (Bayesian inference Using Gibbs Sampling) family of statistical softwares reduces the effort of modeling, since the user must indicate only the prior distributions and the likelihood function. However, in general these softwares do not im- plement several spatial models, although users of WinBUGS and OpenBUGS can enjoy from the spatial add-on called GeoBUGS. JAGS (Just Another Gibbs Sampler), the open-source C++ developed version of the BUGS family, does not contain any function or distribution for spatial modeling. This project aims to fill this gap through the implementation of an extension to the JAGS software, allowing users from different fields to perform a spatial data modeling and analysis.

Área

Geral

Autores

MAGNO TAIRONE DE FREITAS SEVERINO