plotPcorSimulatorJoint: Joint partial correlation matrix simulator plot

Description Usage Arguments Author(s) See Also Examples

Description

graphical representation of two non-zero partial correlation structures

Usage

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

Arguments

x

object of class pcorSimJoint.

minn

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

col

vector defining 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.

...

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

Author(s)

Caballe, Adria <a.caballe@sms.ed.ac.uk>, Natalia Bochkina and Claus Mayer.

See Also

pcorSimulatorJoint for joint partial correlation matrix generation.

Examples

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EX1 <- pcorSimulatorJoint(nobs = 50, nclusters = 2, nnodesxcluster = c(30, 40), 
                         pattern = "pow", diffType = "cluster", dataDepend = "ind", 
                         pdiff = 0.2, diagCCtype = "dicot", diagNZ.strength = .5)
plot(EX1, edgesThickness = TRUE)

EX2 <- pcorSimulatorJoint(nobs = 50, nclusters = 3, nnodesxcluster = c(30, 40,60), 
                          pattern = "pow", diffType = "cluster", dataDepend = "diag", 
                          pdiff = 0.4, diagCCtype = "beta")
plot(EX2)

 

ldstatsHD documentation built on Aug. 14, 2017, 5:06 p.m.