plotCGpvalues: Plot simultaneous p-values for chain graphs
In SIN: A SINful Approach to Selection of Gaussian Graphical Markov Models

Description Usage Arguments Value References See Also Examples

This function plots the simultaneous p-values for SIN model selection for chain graphs.

1	plotCGpvalues(blocks, pvals, legend=TRUE, legendpos=NULL)

`blocks`	a list of integer vectors with entries amongst 1,…,p where p is the number of variables. Each one of the integer vectors specifies a set of variables that form a block in the chain graph. Furthermore, a partial ordering of the variables is specified by the convention that variables in one block are ordered smaller than variables in a block succeeding in the list `blocks`.
`pvals`	a matrix of p-values.
`legend`	a Boolean.
`legendpos`	a numerical vector of length 2.

A plot illustrating the simultaneous p-values. If legend==TRUE, then a legend giving information on the variable labelling is drawn. Optionally, the position of the legend can be specified by legendpos.

Drton, M. \& Perlman, M.D. (2004) Model Selection for Gaussian Concentration Graphs. Biometrika 91(3): 591-602.

Drton, M. \& Perlman, M.D. (2008) A SINful Approach to Gaussian Graphical Model Selection. J. Statist. Plann. Inference 138(4): 1179-1200.

sinCG

data(fowlbones)
blocks <- list(1:2,3:4,5:6)
pvals <- holm(sinCG(blocks,fowlbones$corr,fowlbones$n, type="AMP"))
## Not run: plotCGpvalues(blocks, pvals)
## Not run: plotCGpvalues(blocks, pvals, legend=FALSE)
## Not run: plotCGpvalues(blocks, pvals, legendpos=c(7,0.5))
## Not run: plotCGpvalues(blocks, pvals, legend=TRUE, legendpos=c(7,0.5))