# traceplot: Trace plot of graph size In BDgraph: Bayesian Structure Learning in Graphical Models using Birth-Death MCMC

## Description

Trace plot for graph size for the objects of `S3` class `"bdgraph"`, from function `bdgraph`. It is a tool for monitoring the convergence of the sampling algorithms, BDMCMC and RJMCMC.

## Usage

 `1` ``` traceplot ( bdgraph.obj, acf = FALSE, pacf = FALSE, main = NULL, ... ) ```

## Arguments

 `bdgraph.obj` An object of `S3` class `"bdgraph"`, from function `bdgraph`. `acf` Visualize the autocorrelation functions for graph size. `pacf` Visualize the partial autocorrelations for graph size. `main` Graphical parameter (see plot). `...` System reserved (no specific usage).

## 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:1501.05108

Mohammadi, A. et al (2017). Bayesian modelling of Dupuytren disease by using Gaussian copula graphical models, Journal of the Royal Statistical Society: Series C

Mohammadi, A., Massam H., and G. Letac (2017). The Ratio of Normalizing Constants for Bayesian Graphical Gaussian Model Selection, arXiv preprint arXiv:1706.04416

`bdgraph`
 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## Not run: # Generating multivariate normal data from a 'random' graph data.sim <- bdgraph.sim( n = 50, p = 6, size = 7, vis = TRUE ) bdgraph.obj <- bdgraph( data = data.sim, iter = 10000, burnin = 0, save.all = TRUE ) traceplot( bdgraph.obj ) traceplot( bdgraph.obj, acf = TRUE, pacf = TRUE ) ## End(Not run) ```