Applications to Food Risk Analysis
Quantitative microbiological risk assessment (QMRA) from farm to illness, Campylobacter/chicken, introduction of epidemiologic data in QMRA, exposure assessment considering bacterial genetic diversity, B. cereus/cooked, pasteurised and chilled foods, estimation of microbial contamination, Listeria/fresh vegetables, bacterial inactivation, uncertainty and variability in bacterial growth, Listeria/milk, sensitivity analysis, ochratoxin A.
Bayesian inference, hierarchical modelling, Bayesian meta-analysis, objective/subjective priors, model assessment, Markov chain Monte Carlo methods, sensitivity analysis, predictive model selection, longitudinal binary data models, frailty models.
Combination of expert opinions, interactions between experts, errors model on elicited quantities, elicitation of prior probabilities distributions, posterior distribution given elicited quantities, Bayesian hierarchical modelling, mixture approach, average approach, Dirichlet distribution, pseudo-data.
Monte Carlo simulation, Bootstrap, Markov chain Monte Carlo methods, Gibbs sampler, Metropolis-Hastings algorithm, R programming, OpenBUGS, WinBUGS, Jags.
Generalized Linear Models/Nonlinear models
Weibull model, logit model, mixed model, quasi-likelihood estimating equations, nonlinear regression, least squares estimation, maximum likelihood estimation, variance heterogeneity.
Statistician viewpoint, graphical models, modelling systems, continuous variates, manipulation of Bayesian networks, R package: Rebastaba.