The EU-funded project SCouT deals with order selection and estimation of autoregressive and moving average terms in count time series models by integrating sparsity techniques with the method of composite likelihood estimation. The project aims to enhance the flexibility of time series models for counts and facilitate their application to data characterized by complex dependence structures. Challenging examples arise in the field of temporal and spatial analysis of public health data that will be the main application field of the project. SCouT is carried out under the coordination of the Ca' Foscari University of Venice, Italy and partnership of the Technical University of Dortmund, Germany.
Xanthi Pedeli is the Marie Sklodowska-Curie research fellow. Her research interests include statistical modelling and inference for time series, count data, multivariate models and biostatistics. For the implementation of the SCouT project, Xanthi is hosted at the Ca' Foscari University of Venice. Her curriculum can be found here.
Cristiano Varin is Associate Professor of Statistics at the Ca' Foscari University of Venice. His recent research is focused on composite likelihood inference, copula regression, meta-analysis and paired-comparison modelling. A special interest is the development of open source statistical software in the R programming environment. Cristiano is the supervisor of the SCouT project.
Roland Fried is Full Professor of Statistics in Biosciences at the Technical University of Dortmund. His areas of expertise include biostatistics, modelling of spatial data and time series, online monitoring, robust signal extraction and change point detection. Roland co-supervises the SCouT project.
- 14 October 2016: Invited seminar by X.Pedeli, University of Padova, Department of Statistical Sciences
- 23 October - 19 November 2016: Secondment visit of X. Pedeli to TUDO
- 9 - 11 December 2016: Talk by X. Pedeli (joint work with C. Varin) "Aspects of composite likelihood inference in time series models", CMStatistics2016