GGMnetworkStats.fused {rags2ridges} | R Documentation |
Gaussian graphical model network statistics
Description
Compute various network statistics from a list
sparse precision
matrices. The sparse precision matrix is taken to represent the conditional
independence graph of a Gaussian graphical model. This function is a simple
wrapper for GGMnetworkStats
.
Usage
GGMnetworkStats.fused(Plist)
Arguments
Plist |
A |
Details
For details on the columns see GGMnetworkStats
.
Value
A data.frame
of the various network statistics for each
class. The names of Plist
is prefixed to column-names.
Author(s)
Anders E. Bilgrau, Carel F.W. Peeters <carel.peeters@wur.nl>, Wessel N. van Wieringen
See Also
Examples
## Create some "high-dimensional" data
set.seed(1)
p <- 10
ns <- c(5, 6)
Slist <- createS(ns, p)
## Obtain sparsified partial correlation matrix
Plist <- ridgeP.fused(Slist, ns, lambda = c(5.2, 1.3), verbose = FALSE)
PCsparse <- sparsify.fused(Plist , threshold = "absValue", absValueCut = 0.2)
SPlist <- lapply(PCsparse, "[[", "sparsePrecision") # Get sparse precisions
## Calculate GGM network statistics in each class
## Not run: GGMnetworkStats.fused(SPlist)
[Package rags2ridges version 2.2.7 Index]