Generalized Linear Regression Models on Network-Linked Data with Statistical Inference

Linear regression model and generalized linear models with nonparametric network effects on network-linked observations. The model is originally proposed by Le and Li (2022) and is assumed on observations that are connected by a network or similar relational data structure. A more recent work by Wang, Le and Li (2024) further extends the framework to generalized linear models. All these models are implemented in the current package. The model does not assume that the relational data or network structure to be precisely observed; thus, the method is provably robust to a certain level of perturbation of the network structure. The package contains the estimation and inference function for the model.