R: Plot function for 'S3' class '"graph"'

plot.graph {BDgraph} | R Documentation

## Plot function for `S3` class `"graph"`

### Description

Visualizes structure of the graph.

### Usage

    ## S3 method for class 'graph'
    plot( x, cut = 0.5, mode = "undirected", diag = FALSE, main = NULL,
                          vertex.color = "white", vertex.label.color = 'black', ... )

### Arguments

`x` | An object of `S3` class `"graph"`, from function `graph.sim`.
`cut` | This option is for the case where input 'x' is the object of class "bdgraph" or "ssgraph". Threshold for including the links in the selected graph based on the estimated posterior probabilities of the links.
`mode` | Type of graph which is according to `R` package `igraph`.
`diag` | Logical which is according to `R` package `igraph`.
`main` | Graphical parameter (see plot).
`vertex.color` | The vertex color which is according to `R` package `igraph`.
`vertex.label.color` | The vertex label color which is according to `R` package `igraph`.
`...` | System reserved (no specific usage).

### Author(s)

Reza Mohammadi a.mohammadi@uva.nl

### References

Mohammadi, R. and Wit, E. C. (2019). BDgraph: An `R` Package for Bayesian Structure Learning in Graphical Models, Journal of Statistical Software, 89(3):1-30

Mohammadi, A. and Wit, E. C. (2015). Bayesian Structure Learning in Sparse Gaussian Graphical Models, Bayesian Analysis, 10(1):109-138

Letac, G., Massam, H. and Mohammadi, R. (2018). The Ratio of Normalizing Constants for Bayesian Graphical Gaussian Model Selection, arXiv preprint arXiv:1706.04416v2

Dobra, A. and Mohammadi, R. (2018). Loglinear Model Selection and Human Mobility, Annals of Applied Statistics, 12(2):815-845

Mohammadi, A. et al (2017). Bayesian modelling of Dupuytren disease by using Gaussian copula graphical models, Journal of the Royal Statistical Society: Series C, 66(3):629-645

Mohammadi, A. and Dobra, A. (2017). The `R` Package BDgraph for Bayesian Structure Learning in Graphical Models, ISBA Bulletin, 24(4):11-16

### See Also

`graph.sim`, `bdgraph.sim`

### Examples

    # Generating a 'random' graph
    adj <- graph.sim( p = 10, graph = "random" )
    plot( adj )
    adj

[Package BDgraph version 2.62 Index]