ldstatsHD (version 1.0.1)

plot.wfgl: Joint partial correlation matrix estimator plot

Description

graphical representation of the non-zero joint partial correlation structure.

Usage

# S3 method for wfgl
plot(x, minn = 0, col = c("blue","red","green"), vertex.size = 3,  
      edgesThickness = FALSE, zoomThick = 10, ...)

Arguments

x

object of class wfgl.

minn

used for visualization purposes in very dense networks. It only plots nodes that have degree larger than minn.

col

vector defining estimated edge colors: common edges (first element), only non-zero coefficients for first population (second element) and only non-zero coefficients for second population (third element).

vertex.size

plot.igraph parameter: vertex sizes.

edgesThickness

if TRUE, an edge thickness is proportional to the magnitude of its underlying estimated partial correlation coefficient.

zoomThick

it increases the thickness of all edges by zoomThick times (used for visualization purposes).

…

arguments passed to or from other methods to the low level.

See Also

wfgl for joint estimation of multiple partial correlation matrices.

Examples

# NOT RUN {
EX2   <- pcorSimulatorJoint(nobs =50, nclusters = 3, nnodesxcluster = c(30, 30,30), 
                            pattern = "pow", diffType = "cluster", dataDepend = "diag", 
                            diagCCtype = "dicot", diagNZ.strength = 0.6)
## not run
#wfgl1 <- wfgl(EX2$D1, EX2$D2, lambda1 = 0.01, lambda2 = 0.1, paired = TRUE, 
#              automLambdas = TRUE, sigmaEstimate = "CRmad", 
#              pairedEst = "Reg-based-sim", maxiter = 30)
#plot(wfgl1)
#plot(wfgl1, minn = 1, edgesThickness = TRUE)


# }