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.
Can M. Le and Tianxi Li.
Maintainer: Tianxi Li <tianxili@umn.edu>
| Package: | NetworkReg |
| Type: | Package |
| Version: | 1.1 |
| Date: | 2024-02-02 |
| License: | GPL (>= 2) |
Can M. Le and Tianxi Li. 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.