- Bayesian Estimation of Epidemiological Models: Methods, Causality, and . . .
We present a general framework for Bayesian estimation and causality assessment in epidemiological models The key to our approach is the use of sequential Monte Carlo methods to evaluate the likelihood of a generic epidemiological model Once we have the likelihood, we specify priors and rely on a Markov chain Monte Carlo to sample from the posterior distribution We show how to use the posterior simulation outputs as inputs for exercises in causality assessment We apply our approach to
|