Mukhsar, Asrul Sani, Bahriddin Abapihi, Edi Cahyono
Bayesian, dengue hemorrhagic fever, posterior distribution, score as count, zero exceeds, ZIP
Response variables are scored as counts, for example, dengue hemorrhagic fever (DHF) number cases exposed in densely population of urban areas of Indonesia, for example in Kendari city as the capital of Southeast Sulawesi Province, are often arise in Bayesian analysis. At a certain time is not found (or zero) the DHF cases in the case, but other times appear number of DHF cases. When the number of zeros exceeds the amount expected such as under the Poisson density, the zero inflated Poisson (ZIP) model is more appropriate. In using the ZIP model in DHF studies, it is necessary to accommodate local environmental characters as predictors. This study is proposing a Bayesian mixture ZIP spatio-temporal (BMZIP S-T) model and to construct its posterior distribution.
Cite this paper
Mukhsar, Asrul Sani, Bahriddin Abapihi, Edi Cahyono. (2016) Construction Posterior Distribution for Bayesian Mixed ZIP Spatio-Temporal Model. International Journal of Biology and Biomedicine, 1, 32-39