BDgraph (version 2.22)

prob: Posterior probabilities of the graphs

Description

Provides the posterior probabilities for the 'g' most likely graphs or a specific graph, 'G'.

Usage

prob( output, g = 4, G = NULL )

Arguments

output

An object of S3 class "bdgraph", from function bdgraph.

g

The number of graphs with the highest posterior probabilities to be shown (default is 4). This option is ignored if 'G' is specified.

G

Adjacency matrix corresponding to a graph structure. It is an upper triangular matrix in which $g_{ij}=1$ if there is a link between notes $i$ and $j$, otherwise $g_{ij}=0$. It also can be an object of S3 class

Value

• best.G
  The graphs with the highest posterior probabilities.
• prob.G
  A vector of the posterior probabilities of the graphs corresponding to 'best.G'.

References

Mohammadi, A. and E. Wit (2015). Bayesian Structure Learning in Sparse Gaussian Graphical Models, Bayesian Analysis, 10(1):109-138 Mohammadi, A. and E. Wit (2015). BDgraph: An R Package for Bayesian Structure Learning in Graphical Models, Arxiv preprint arXiv:1501.05108v2 Mohammadi, A., F. Abegaz Yazew, E. van den Heuvel, and E. Wit (2015). Bayesian Modeling of Dupuytren Disease Using Gaussian Copula Graphical Models, Arxiv preprint arXiv:1501.04849v2

See Also

bdgraph

Examples

# generating multivariate normal data from a 'random' graph
data.sim <- bdgraph.sim( n = 50, p = 6, size = 6, vis = TRUE )

output   <- bdgraph( data = data.sim )

# Estimated posterior probability of the true graph
prob( output, G = data.sim )

# Estimated posterior probability of the first and second graphs with highest probabilities
prob( output, g = 2 )