NetworkReg-package

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

Linear regression model with nonparametric network effects on network-linked observations. The model is proposed by Le and Li (2022) arXiv:2007.00803 on observations that are connected by a network or similar relational data structure. 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. package

Details

Package:	NetworkReg
Type:	Package
Version:	2.0
Date:	2024-10-10
License:	GPL (>= 2)

References

Le, C. M., & Li, T. (2022). Linear regression and its inference on noisy network-linked data. Journal of the Royal Statistical Society Series B: Statistical Methodology, 84(5), 1851-1885.

Wang J, Le C M, Li T. Perturbation-Robust Predictive Modeling of Social Effects by Network Subspace Generalized Linear Models. arXiv preprint arXiv:2410.01163, 2024.

Author(s)

Jianxiang Wang, Can M. Le, and Tianxi Li.

Maintainer: Jianxiang Wang jw1881@scarletmail.rutgers.edu