Modeling group heterogeneity in spatio-temporal data via physics-informed semiparametric regression
基于物理信息半参数回归的时空数据组异质性建模
In this work we propose a novel approach for modeling spatio-temporal data characterized by group structures. In particular, we extend classical mixed effect regression models by introducing a space-time nonparametric component, regularized through a partial differential equation, to embed the physical dynamics of the underlying process, while random effects capture latent variability associated with the group structure present in the data. We propose a two-step procedure to…