PartialNetwork: Estimating Peer Effects Using Partial Network Data

Implements IV-estimator and Bayesian estimator for linear-in-means Spatial Autoregressive (SAR) model (see LeSage, 1997 <>; Lee, 2004 <>; Bramoullé et al., 2009 <doi:10.1016/j.jeconom.2008.12.021>), while assuming that only a partial information about the network structure is available. Examples are when the adjacency matrix is not fully observed or when only consistent estimation of the network formation model is available (see Boucher and Houndetoungan <>).

Version: 1.0.2
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.0), Formula,, abind, Matrix, parallel, doParallel, foreach, doRNG
LinkingTo: Rcpp, RcppArmadillo (≥, RcppEigen, RcppNumerical, RcppProgress
Suggests: AER, knitr, rmarkdown, CDatanet, ggplot2, MASS
Published: 2023-08-22
Author: Vincent Boucher [aut], Elysee Aristide Houndetoungan [cre, aut]
Maintainer: Elysee Aristide Houndetoungan <ariel92and at>
License: GPL-3
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: PartialNetwork results


Reference manual: PartialNetwork.pdf
Vignettes: PartialNetwork package: Examples and Applications


Package source: PartialNetwork_1.0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): PartialNetwork_1.0.2.tgz, r-oldrel (arm64): PartialNetwork_1.0.2.tgz, r-release (x86_64): PartialNetwork_1.0.2.tgz


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