The objective of our group is the methodological and applied research of Bayesian Statistics, especially in scenarios of epidemiological and environmental type. Our work is fundamentally based on three axes:
- Hierarchical models in studies with correlated data.
- Model selection.
- Computational simulation models.
All of them are somewhat mixed in nature, methodological and applied, and in the compatibility and interrelation of many of their knowledge and objectives.
The first thematic block is the most extensive and is dedicated to research on models with correlated data associated with structures of a spatial-temporal, longitudinal, survival or non-survival type, and of blood kinship. Methodological research in disease mapping has a long tradition in our team, currently with unbalanced multivariate and spatial-temporal objectives. This block also contains new research proposals dedicated to joint models with longitudinal and survival data, methodology on species distribution, spatial-temporal surveillance of diseases and regression methods for scattered genetic data from genetically isolated populations with known family trees, which will undoubtedly lead us to Big Data.
In the area dedicated to the selection of models, marginal, conditioned, and combined measures are studied to quantify the contribution of a potential set of covariates in the explanation of a response of interest, and two new lines have been initiated, with a more applied orientation, which link the subject of variable selection with longitudinal and survival models and related data through structures of consanguinity.
Finally, in the block of computational models, the group continues with a line of action dedicated to the calibration of multivariate computational models and the implementation of the results obtained in a computer application and in a new application dedicated to uncertainty modelling in compartmental models.
The research group in Public Opinión and Elections aims at analyzing, studying and finding solutions to all issues and questions related to electoral processes and/or the measurement and monitoring of public opinion, applying the most advanced quantitative techniques.
The most relevant research fields of the group include (but are not limited to) the following: the generation of electoral predictions, inference of individual voting behavior, analysis of polls and surveys, the search of new methodological approaches to improve (reducing costs) the quality of sampling methods, semantic analysis of opinions and monitoring of the internet sentiment, the study of the consequences of non-response and of the biases introduced during the whole inference process, the solution to the gaps in the databases, the integration and pooling of local and global information to obtain multilevel responses, and the development of statistcal theory and methodology.
The approach used in the research group in Public Opinión and Elections is open, not being limited by any particular methodological tendency, and makes extensive use of whatever sources of information. Thus, we use classical and Bayesian techniques, we apply from simple linear regression models to complex approaches based on neural networks, wavelets or auto-binomial models, we use the spatial and/or temporal component of the data explicitly, we perform simulation via Markov chain Monte Carlo or directly by Monte Carlo methods, and we introduce in our models survey data, reported election results, news reports, internet messages and/or official statistics.
The members of the group are open to working with other research groups, companies and institutions and encourage interested parties to contact us in order to explore possible avenues of collaboration.
