plotcoda: Convergence plot

Description

Displays a plot which provides the cumulative occupancy fractions of all possible links in the graph. The plot can be used for monitoring the convergence of the BD-MCMC sampling algorithm.

Usage

plotcoda( output, thin = NULL, main = NULL, links = TRUE, ... )

Arguments

output

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

thin

An option for getting fast result for a cumulative plot according to part of the iteration.

main

Graphical parameter (see plot).

links

Logical: if TRUE and number of variables (p) is more that 15, you will see a plot result for 100 selected links. The default is TRUE.

...

System reserved (no specific usage).

Details

Note that a spending time for this function depends on the number of nodes. It should be slow for the high-dimensional graphs. For fast faster, you can choose bigger value than other alternatives for the 'thin' option.

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

Examples

Run this code

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

output <- bdgraph( data = data.sim, iter = 10000, burnin = 0  )

plotcoda( output )