plinks {BDgraph} | R Documentation |
Provides the estimated posterior link probabilities for all possible links in the graph.
plinks( bdgraph.obj, round = 2, burnin = NULL )
bdgraph.obj |
An object of |
round |
A value for rounding all probabilities to the specified number of decimal places. |
burnin |
The number of burn-in iteration to scape. |
An upper triangular matrix which corresponds the estimated posterior probabilities for all possible links.
Reza Mohammadi a.mohammadi@uva.nl and Ernst Wit
Mohammadi, R. and Wit, E. C. (2019). BDgraph: An R
Package for Bayesian Structure Learning in Graphical Models, Journal of Statistical Software, 89(3):1-30
Mohammadi, A. and Wit, E. C. (2015). Bayesian Structure Learning in Sparse Gaussian Graphical Models, Bayesian Analysis, 10(1):109-138
Letac, G., Massam, H. and Mohammadi, R. (2018). The Ratio of Normalizing Constants for Bayesian Graphical Gaussian Model Selection, arXiv preprint arXiv:1706.04416v2
Dobra, A. and Mohammadi, R. (2018). Loglinear Model Selection and Human Mobility, Annals of Applied Statistics, 12(2):815-845
Mohammadi, A. et al (2017). Bayesian modelling of Dupuytren disease by using Gaussian copula graphical models, Journal of the Royal Statistical Society: Series C, 66(3):629-645
## Not run: # Generating multivariate normal data from a 'circle' graph data.sim <- bdgraph.sim( n = 70, p = 6, graph = "circle", vis = TRUE ) bdgraph.obj <- bdgraph( data = data.sim, iter = 10000 ) plinks( bdgraph.obj, round = 2 ) ## End(Not run)