Linear regression and its inference on noisy network-linked data

Understand

Linear regression on network-linked observations has been an essential tool in modeling the relationship between response and covariates with additional network structures.

• Previous methods either lack inference tools or rely on restrictive assumptions on social effects and usually assume that networks are observed without errors.
• This paper proposes a regression model with nonparametric network effects.
• The model does not assume that the relational data or network structure is exactly observed and can be provably robust to network perturbations.