SEMgraph: Network Analysis and Causal Inference Through Structural Equation Modeling

Estimate networks and causal relationships in complex systems through Structural Equation Modeling. This package also includes functions to import, weight, manipulate, and fit biological network models within the Structural Equation Modeling framework; Palluzzi and Grassi (2021) <arXiv:2103.08332>.

Version: 1.0.3
Depends: igraph (≥ 1.2.1), lavaan (≥ 0.5-23), R (≥ 4.0)
Imports: boot (≥ 1.3-25), cate (≥ 1.0.4), corpcor (≥ 1.6.9), dagitty (≥ 0.3-0), diffusr (≥ 0.1.4), flip (≥ 2.5.0), gdata (≥ 2.18.0), ggm (≥ 2.3), GGMncv (≥ 2.0.0), glmnet (≥ 2.0-18), graph (≥ 1.56.0), Matrix (≥ 1.3-0), pbapply (≥ 1.4-3), protoclust (≥ 1.6.3), RcppEigen (≥ 0.3.3.4.0), Rgraphviz (≥ 2.22.0)
Suggests: huge, pcalg, graphite, org.Hs.eg.db
Published: 2021-07-08
Author: Mario Grassi [aut], Fernando Palluzzi [aut, cre], Daniele Pepe [ctb]
Maintainer: Fernando Palluzzi <fernando.palluzzi at gmail.com>
License: GPL-3
URL: https://github.com/fernandoPalluzzi/SEMgraph
NeedsCompilation: no
Materials: README
CRAN checks: SEMgraph results

Downloads:

Reference manual: SEMgraph.pdf
Package source: SEMgraph_1.0.3.tar.gz
Windows binaries: r-devel: SEMgraph_1.0.3.zip, r-release: SEMgraph_1.0.3.zip, r-oldrel: SEMgraph_1.0.3.zip
macOS binaries: r-release (arm64): SEMgraph_1.0.3.tgz, r-release (x86_64): SEMgraph_1.0.3.tgz, r-oldrel: SEMgraph_1.0.3.tgz

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