A Common Platform for Graphical Models in R: The gRbase Package
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DOI: http://hdl.handle.net/10.18637/jss.v014.i17
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References listed on IDEAS
- Badsberg, Jens Henrik, 2001. "A Guide to CoCo," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 6(i04).
- Boettcher, Susanne G. & Dethlefsen, Claus, 2003. "deal: A Package for Learning Bayesian Networks," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 8(i20).
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Cited by:
- Kalisch, Markus & Mächler, Martin & Colombo, Diego & Maathuis, Marloes H. & Bühlmann, Peter, 2012. "Causal Inference Using Graphical Models with the R Package pcalg," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i11).
- Djordjilović, Vera & Chiogna, Monica, 2022. "Searching for a source of difference in graphical models," Journal of Multivariate Analysis, Elsevier, vol. 190(C).
- Lagani, Vincenzo & Athineou, Giorgos & Farcomeni, Alessio & Tsagris, Michail & Tsamardinos, Ioannis, 2017.
"Feature Selection with the R Package MXM: Discovering Statistically Equivalent Feature Subsets,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 80(i07).
- Lagani, Vincenzo & Athineou, Giorgos & Farcomeni, Alessio & Tsagris, Michail & Tsamardinos, Ioannis, 2016. "Feature Selection with the R Package MXM: Discovering Statistically-Equivalent Feature Subsets," MPRA Paper 72772, University Library of Munich, Germany.
- Marchetti, Giovanni M., 2006. "Independencies Induced from a Graphical Markov Model After Marginalization and Conditioning: The R Package ggm," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 15(i06).
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