Spatio-temporal modelling has largely been developed through applications in geostatistics, hydrology and meteorology. More recent activities in the area include environment monitoring, tracking, functional MRI, health data and dynamic shape analysis. Motivated by these applications, the field has adopted various modelling strategies, essentially depending on the underlying objective of the analysis, the scale and type of data. This talk is concerned with the specification of a reduced-rank regression model which warrants consideration when data sets showing different types of spatial complexities are available. Details on data analysis in several research fields will be given.
This talk is part of joint works with Lara Fontanella, Rosalba Ignaccolo and Pasquale Valentini