Simulates an contemporaneous and temporal network using the method described by Yin and Li (2001)
randomGVARmodel(Nvar, probKappaEdge = 0.1, probKappaPositive = 0.5, probBetaEdge = 0.1,
probBetaPositive = 0.5, maxtry = 10, kappaConstant = 1.1)A list containing:
True kappa structure (residual inverse variance-covariance matrix)
True beta structure
True partial contemporaneous correlations
True partial temporal correlations
Number of variables
Probability of an edge in contemporaneous network
Proportion of positive edges in contemporaneous network
Probability of an edge in temporal network
Propotion of positive edges in temporal network
Maximum number of attempts to create a stationairy VAR model
The constant used in making kappa positive definite. See Yin and Li (2001)
Sacha Epskamp
The resulting simulated networks can be plotted using the plot method.
Yin, J., & Li, H. (2011). A sparse conditional gaussian graphical model for analysis of genetical genomics data. The annals of applied statistics, 5(4), 2630-2650.