plotcoda: Convergence plot

Description

Visualizes the cumulative occupancy fractions of all possible links in the graph. It can be used for monitoring the convergence of the sampling algorithms, BDMCMC and RJMCMC.

Usage

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

Arguments

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 is more that 15, then 100 links randomly is selected for visualization. The default is TRUE.

...

System reserved (no specific usage).

Details

Note that a spending time for this function depends on the number of nodes.For fast result, you can choose bigger value 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:1501.05108 Mohammadi, A., F. Abegaz Yazew, E. van den Heuvel, and E. Wit (2015). Bayesian Gaussian Copula Graphical Modeling for Dupuytren Disease, arXiv:1501.04849

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 , save.all = TRUE )
   
plotcoda( output )