Modern Toolbox for Spatial and Functional Data

patial and functional data analysis has become increasingly important across environmental sciences, economics, finance, and many other fields where complex data structures are now routinely collected. Spatial data can appear in several forms: in some applications they are aggregated over regions or lattices and can be described using classical spatial models; in others they are observed continuously over space, as in air pollution or climate studies, where ideas from functional data analysis provide a natural framework. Functional data methods themselves have a wide and well-developed literature, with applications ranging from modelling curves and surfaces to analysing dynamic processes such as volatility or yield curves. While both areas are broad, this course focuses on a selection of classical models together with a few recent developments, offering an introductory yet coherent view of how these tools are used in practice.