https://bayesian-graphical-modelling-lab.r-universe.devRecent package updates in bayesian-graphical-modelling-labR-universehttps://github.com/bayesian-graphical-modelling-lab.pnghttps://bayesian-graphical-modelling-lab.r-universe.devMon, 08 Jun 2026 08:58:48 GMTm.marsman@uva.nl (Maarten Marsman)Bayesian estimation and edge selection for graphical models of mixed binary, ordinal, and continuous variables. The variable types determine the model: an ordinal Markov random field for discrete data, a Gaussian graphical model for continuous data, or a mixed Markov random field combining both. Edge inclusion is determined through spike-and-slab priors, yielding posterior inclusion probabilities for each edge. Supports multi-group comparison via 'bgmCompare()', simulation, prediction, and missing data imputation.https://github.com/r-universe/bayesian-graphical-modelling-lab/actions/runs/27131598878Mon, 08 Jun 2026 08:58:48 GMTbgms0.2.0.0successhttps://bayesian-graphical-modelling-lab.r-universe.devhttps://github.com/bayesian-graphical-modelling-lab/bgmsdiagnostics.Rmddiagnostics.htmlDiagnostics and Spike-and-Slab Summaries2025-09-23 14:55:272026-06-03 20:32:59intro.Rmdintro.htmlGetting Started with bgms2025-09-23 14:55:272026-06-03 20:32:59comparison.Rmdcomparison.htmlModel Comparison with bgmCompare2025-09-23 14:55:272026-03-04 14:44:29