BDgraph (version 2.57)

plinks: Estimated posterior link probabilities

Description

Provides the estimated posterior link probabilities for all possible links in the graph.

Usage

plinks( bdgraph.obj, round = 2, burnin = NULL )

Arguments

bdgraph.obj

An object of S3 class "bdgraph", from function bdgraph. It also can be an object of S3 class "ssgraph", from the function ssgraph of R package ssgraph.

round

A value for rounding all probabilities to the specified number of decimal places.

burnin

The number of burn-in iteration to scape.

Value

p_links

An upper triangular matrix which corresponds the estimated posterior probabilities for all possible links.

References

Mohammadi, A. and Wit, E. C. (2015). Bayesian Structure Learning in Sparse Gaussian Graphical Models, Bayesian Analysis, 10(1):109-138

Mohammadi, A. and Wit, E. C. (2017). BDgraph: An R Package for Bayesian Structure Learning in Graphical Models, arXiv preprint arXiv:1501.05108v5

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

See Also

bdgraph, bdgraph.mpl

Examples

# 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 )
# }