BDgraph (version 2.13)

plotcoda: Convergence plot

Description

This function according to "bdgraph" output gives us several plots. These plots can be used to check the convergence of the BD-MCMC algorithm.

Usage

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

Arguments

output

An object with S3 class "bdgraph"

thin

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

trace

Logical: if TRUE (default), tracing information is printed.

main

Graphical parameter (see plot).

...

System reserved (no specific usage).

Details

Note that a spending time for this function depends on the graph. It should be slow for the high-dimensional graphs. To make it faster you can choose bigger value for 'thin'.

References

Mohammadi, A. and Wit, E. C. (2014). Bayesian structure learning in sparse Gaussian graphical models, Bayesian Analysis, acceped. http://arxiv.org/abs/1210.5371v6

See Also

bdgraph

Examples

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