bf {BDgraph}R Documentation

Bayes factor between two graphs

Description

Compute the Bayes factor between the structure of two graphs.

Usage

 
    bf( num, den, bdgraph.obj, log = TRUE ) 

Arguments

num, den

An adjacency matrix corresponding to the true graph structure in which a_{ij}=1 if there is a link between notes i and j, otherwise a_{ij}=0. It can be an object with S3 class "graph" from function graph.sim. It can be an object with S3 class "sim" from function bdgraph.sim.

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::ssgraph() of R package ssgraph::ssgraph().

log

A character value. If TRUE the Bayes factor is given as log(BF).

Value

A single numeric value, the Bayes factor of the two graph structures num and den.

Author(s)

Reza Mohammadi a.mohammadi@uva.nl

References

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

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

See Also

bdgraph, bdgraph.mpl, compare, bdgraph.sim

Examples

    ## Not run: 
        # Generating multivariate normal data from a 'circle' graph
        data.sim <- bdgraph.sim( n = 50, p = 6, graph = "circle", vis = TRUE )

        # Running sampling algorithm
        bdgraph.obj <- bdgraph( data = data.sim )

        graph_1 <- graph.sim( p = 6, vis = TRUE )
        graph_2 <- graph.sim( p = 6, vis = TRUE )

        bf( num = graph_1, den = graph_2, bdgraph.obj = bdgraph.obj )
    
## End(Not run)

[Package BDgraph version 2.64 Index]