Description Usage Arguments Author(s) References See Also Examples

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.

1 |

`bdgraph.obj` |
An object of |

`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). |

Abdolreza Mohammadi and Ernst Wit

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*

Dobra, A. and A. Mohammadi (2017). Loglinear Model Selection and Human Mobility, *arXiv preprint arXiv:1711.02623*

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*

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)
``` |

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