Linear regression model with nonparametric network effects on network-linked observations. The model is proposed by Le and Li (2020) <arXiv:2007.00803> and is assumed 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.
| Version: | 1.0 |
| Imports: | Matrix, stats, methods, randnet, RSpectra |
| Published: | 2020-07-07 |
| Author: | Can M. Le, Tianxi Li |
| Maintainer: | Tianxi Li <tianxili at virginia.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | NetworkReg results |
| Reference manual: | NetworkReg.pdf |
| Package source: | NetworkReg_1.0.tar.gz |
| Windows binaries: | r-devel: NetworkReg_1.0.zip, r-release: NetworkReg_1.0.zip, r-oldrel: NetworkReg_1.0.zip |
| macOS binaries: | r-release: NetworkReg_1.0.tgz, r-oldrel: NetworkReg_1.0.tgz |
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