link2adj {BDgraph} | R Documentation |
Extract links from an adjacency matrix or an object of calsses "sim"
from function bdgraph.sim
and
"graph"
from function graph.sim
.
link2adj( link, p = NULL )
link |
An (2 \times p) |
p |
The number of nodes of the graph. |
An adjacency matrix corresponding to a graph structure in which a_{ij}=1 if there is a link between notes i and j, otherwise a_{ij}=0.
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
Letac, G., Massam, H. and Mohammadi, R. (2018). The Ratio of Normalizing Constants for Bayesian Graphical Gaussian Model Selection, arXiv preprint arXiv:1706.04416v2
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
Dobra, A. and Mohammadi, R. (2018). Loglinear Model Selection and Human Mobility, Annals of Applied Statistics, 12(2):815-845
Pensar, J. et al (2017) Marginal pseudo-likelihood learning of discrete Markov network structures, Bayesian Analysis, 12(4):1195-215
# Generating a 'random' graph adj <- graph.sim( p = 6, vis = TRUE ) link <- adj2link( adj ) link2adj( link, p = 6 )