Bayesian inference of graph-based dependencies from mixed-type data
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DOI: 10.1016/j.jmva.2024.105323
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- Fellinghauer, Bernd & Bühlmann, Peter & Ryffel, Martin & von Rhein, Michael & Reinhardt, Jan D., 2013. "Stable graphical model estimation with Random Forests for discrete, continuous, and mixed variables," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 132-152.
- Anindya Bhadra & Bani K. Mallick, 2013. "Joint High-Dimensional Bayesian Variable and Covariance Selection with an Application to eQTL Analysis," Biometrics, The International Biometric Society, vol. 69(2), pages 447-457, June.
- Castelletti, Federico & Peluso, Stefano, 2021. "Equivalence class selection of categorical graphical models," Computational Statistics & Data Analysis, Elsevier, vol. 164(C).
- Shizhe Chen & Daniela M. Witten & Ali Shojaie, 2015. "Selection and estimation for mixed graphical models," Biometrika, Biometrika Trust, vol. 102(1), pages 47-64.
- Dasgupta, Tirthankar & Ma, Christopher & Joseph, V. Roshan & Wang, Z.L. & Wu, C. F. Jeff, 2008. "Statistical Modeling and Analysis for Robust Synthesis of Nanostructures," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 594-603, June.
- Abdolreza Mohammadi & Fentaw Abegaz & Edwin Heuvel & Ernst C. Wit, 2017. "Bayesian modelling of Dupuytren disease by using Gaussian copula graphical models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(3), pages 629-645, April.
- Martin, Andrew D. & Quinn, Kevin M. & Park, Jong Hee, 2011. "MCMCpack: Markov Chain Monte Carlo in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i09).
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Keywords
Bayesian inference; Conditional Gaussian distribution; Mixed variables; Structure learning; Undirected graph;All these keywords.
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