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Add: R: qgraph tutorial and examples

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François Briatte 2016-11-06 19:19:27 +01:00
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@ -608,7 +608,9 @@ Inspired by [Awesome Deep Learning](https://github.com/ChristosChristofidis/awes
- [PAFit](https://cran.r-project.org/web/packages/PAFit/) - Nonparametric estimation of preferential attachment and node fitness in temporal complex networks. - [PAFit](https://cran.r-project.org/web/packages/PAFit/) - Nonparametric estimation of preferential attachment and node fitness in temporal complex networks.
- [PCIT](https://cran.r-project.org/web/packages/PCIT/) - Implements Partial Correlation with Information Theory in order to identify meaningful correlations in weighted networks, such as gene co-expression networks. - [PCIT](https://cran.r-project.org/web/packages/PCIT/) - Implements Partial Correlation with Information Theory in order to identify meaningful correlations in weighted networks, such as gene co-expression networks.
- [RCy3](https://bioconductor.org/packages/release/bioc/html/RCy3.html) - Interface between R and recent versions of Cytoscape. - [RCy3](https://bioconductor.org/packages/release/bioc/html/RCy3.html) - Interface between R and recent versions of Cytoscape.
- [qgraph](https://cran.r-project.org/web/packages/qgraph/) - Tools to model and visualize psychometric networks; also aimed at weighted graphical models. - [qgraph](https://cran.r-project.org/web/packages/qgraph/) - Tools to model and visualize psychometric networks; also aimed at weighted graphical models).
- [Network Model Selection Using qgraph 1.3](http://psychosystems.org/network-model-selection-using-qgraph-1-3-10/) (2014).
- [qgraph Examples](http://sachaepskamp.com/qgraph/examples)
- [relevent](https://cran.r-project.org/web/packages/relevent/) - Tools to fit relational event models (REM). - [relevent](https://cran.r-project.org/web/packages/relevent/) - Tools to fit relational event models (REM).
- [rem](https://cran.r-project.org/web/packages/rem/) - Estimate endogenous network effects in event sequences and fit relational event models (REM), which measure how networks form and evolve over time. - [rem](https://cran.r-project.org/web/packages/rem/) - Estimate endogenous network effects in event sequences and fit relational event models (REM), which measure how networks form and evolve over time.
- [rgexf](https://cran.r-project.org/web/packages/rgexf/) - Export network objects from R to GEXF for manipulation with software like Gephi or Sigma. - [rgexf](https://cran.r-project.org/web/packages/rgexf/) - Export network objects from R to GEXF for manipulation with software like Gephi or Sigma.