plot.ssgraph | R Documentation |
S3
class "ssgraph"
Visualizes structure of the selected graphs which could be a graph with links for which their estimated posterior probabilities are greater than 0.5 or graph with the highest posterior probability.
## S3 method for class 'ssgraph' plot( x, cut = 0.5, ... )
x |
An object of |
cut |
Threshold for including the links in the selected graph based on the estimated posterior probabilities of the links; See the examples. |
... |
System reserved (no specific usage). |
Reza Mohammadi a.mohammadi@uva.nl
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
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
ssgraph
## Not run: # Generating multivariate normal data from a 'scale-free' graph data.sim <- bdgraph.sim( n = 60, p = 7, graph = "scale-free", vis = TRUE ) ssgraph.obj <- ssgraph( data = data.sim ) plot( ssgraph.obj ) plot( ssgraph.obj, cut = 0.3 ) ## End(Not run)
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