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 proposed in
Grassi M, Palluzzi F, Tarantino B (2022) <doi:10.1093/bioinformatics/btac567>.
| Version: |
1.2.1 |
| Depends: |
igraph (≥ 1.6.0), lavaan (≥ 0.6-1), R (≥ 4.0) |
| Imports: |
aspect, boot, corpcor, dagitty, flip, gdata, ggm, glasso, glmnet, graph, mgcv, mvtnorm, pbapply, protoclust, RBGL, Rgraphviz |
| Published: |
2024-02-06 |
| Author: |
Mario Grassi [aut],
Fernando Palluzzi [aut],
Barbara Tarantino [aut, cre] |
| Maintainer: |
Barbara Tarantino <barbara.tarantino01 at universitadipavia.it> |
| License: |
GPL-3 |
| URL: |
https://github.com/fernandoPalluzzi/SEMgraph |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
SEMgraph results |
Documentation:
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