NetworkReg

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) doi:10.48550/arXiv.2007.00803 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) doi:10.48550/arXiv.2410.01163 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.

Last 30 days

This package has been downloaded 413 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 48 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 3,540 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Feb 20, 2025 with 53 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.