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  Full Conditional Distribution Investigation of Bayesian Poisson Lognormal 2-Level Spatiotemporal for Analyzing DHF Risk  
Diupload oleh : NUR Iriawan,Prof.,Drs.,MIKom.,Ph.D.
Pengarang : Mukhsar, Iriawan, N, Ulama, B. S. S, Sutikno, Kuswanto H
Tahun : 2013
Dipublikasikan di :
Jenis Jurnal : International Conference
Eksternal Link : http://basic.ub.ac.id/web/sites/default/files/eproceeding2013/Mathematics/M29.pdf
Bidang Penelitian : Statistics Computation and Modeling
Abstrak : Risk modeling of Dengue hemorrhagic fever (DHF) cases is framed by some factors, such as spatial heterogeneity, uncertainty components (or random effects), DHF nested within two levels, and spatiotemporal varying. Nested factor could happen such as DHF nested to location as level 1 and location nested to population as level 2. This study develops and analyzes spatial convolution (Poisson - Lognormal) model using Bayesian approach, called Bayesian Poisson-Lognormal 2-level (BP2L) spatiotemporal. In this model, spatial terms are treated as random effects factors (namely uncorrelated and correlated). BP2L spatiotemporal is a complex model, so the parameter estimation needs the computational intensive approach. It requires mathematical manipulation such as full conditional distribution form gathered from its joint posterior in order to estimate those parameters through Gibbs sampler or Metropolis-Hasting. The investigationresult showed that full conditional distribution of model is closed form. Gibbs sampler, therefore, is a right method for estimating the parameters
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