Dados do Trabalho
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