- Longitudinal and survival data joint models.Longitudinal and survival data joint models with time or survival targets are studied, with special emphasis on dynamic predictive targets.
- Spatio-temporal disease surveillance.Development of statistical methodologies for the rapid and reliable detection of influenza epidemics. We approach the inference and prediction of these models from the Bayesian paradigm, which allows the implementation of complex models with spatial, temporal and hierarchical structures.
- Species distribution models.Development of models to predict the spatial and spatial-temporal distribution of species. The incorporation of uncertainty in covariates, the problems generated by missing values, the effect of preferential sampling and the handling of large volumes of data are addressed.
- Model selection.Our group addresses the problem of model selection from a Bayesian target point of view. We particularly work on the study of criteria that allow us to establish optimal prior distributions in order to carry out an effective selection and modeling.
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