Statistical Data Science group (SDS)
- Grupos de investigación
- Economics
- Statistical Data Science group (SDS)
- Group head:
- Aurea Grané Chávez, David Delgado Gómez
- Email:
- agrane@est-econ.uc3m.es, ddelgado@est-econ.uc3m.es
Description
The main goal of this group is to provide solutions to real problems, whose common link is the complexity of the data sets they involve. As an example, some challenges that the research members have already faced are obtaining an early diagnosis of certain mental health illnesses, monitoring the evolution of health and dependency risk of the elderly living in different regions and territories, or monitoring emergency management, among others. All of these problems involve information of very different types, such as heterogeneous multivariate data, textual data, functional data, manifolds or even a combination of all of them. In this research group, statistical learning techniques based on distances and depths are developed and used as tools for visualization, monitoring and prediction in massive data sets of a certain complexity.
Lines of research
- Design and development of robust prediction and classification tools for weighted data, and viable for massive data
- Design of protocols for analysis and visualization of the temporal and spatial evolution of phenomena of interest
- Development of unsupervised statistical learning techniques for obtaining robust profiles
- Development of imputation techniques from point depths
- Design and development of functional time series visualization tools
- Outlier detection techniques for heterogeneous multivariate weighted data
- Outlier detection techniques in functional time series
- Software development in R, Matlab and Python
Contact email: research@uc3m.es