A Spatial functional Approach for Curve Classification A Spanish firms’ panel data analysis

This paper proposes a spatial functional formulation of the normal mixed effect model for the statistical classification of spatially dependent Gaussian curves. Fixed effect parameters are represented in terms of a functional mul- tiple regression model whose regression operators can change in space. Local spatial homogeneity of these operators is measured in terms of their Hilbert- Schmidt distances, leading to the classification of fixed effect curves in dif- ferent groups. A real data example in the financial context is analyzed as an illustration.