Author: Sangeeta Bhatia; Britta Lassmann; Emily Cohn; Malwina Carrion; Moritz U.G. Kraemer; Mark Herringer; John Brownstein; Larry Madoff; Anne Cori; Pierre Nouvellet
Title: Using Digital Surveillance Tools for Near Real-Time Mapping of the Risk of International Infectious Disease Spread: Ebola as a Case Study Document date: 2019_11_15
ID: jwesa12u_95
Snippet: Model fitting was done in a Bayesian framework using a Markov Chain Monte Carlo (MCMC) as implemented in the software Stan [41] and its R interface rstan [42] . We ran 2 MCMC chains with 3000 iterations and burn-in of 1000 iterations. Convergence of MCMC chains was confirmed using visual inspections of the diagnostics (Potential Scale Reduction Factor [43] and Geweke Diagnostics [44]) reported by R package ggmcmc [45] . An example report produced.....
Document: Model fitting was done in a Bayesian framework using a Markov Chain Monte Carlo (MCMC) as implemented in the software Stan [41] and its R interface rstan [42] . We ran 2 MCMC chains with 3000 iterations and burn-in of 1000 iterations. Convergence of MCMC chains was confirmed using visual inspections of the diagnostics (Potential Scale Reduction Factor [43] and Geweke Diagnostics [44]) reported by R package ggmcmc [45] . An example report produced by ggmcmc is included in the Supplementary Material.
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