See arxiv.org/abs/1609.04156 for details.
simMLgvar(nTime, nVar, nPerson, propPositive = 0.5, kappaRange = c(0.25, 0.5),
betaRange = c(0.25, 0.5), betweenRange = c(0.25, 0.5),
rewireWithin = 0, betweenVar = 1, withinVar = 0.25,
temporalOffset = 2)A "simMLgvar" object with the following elements:
Generated dataset
Fixed inverse contemporaneous covariance matrix
Fixed contemporaneous partial correlation network
Fixed temporal network
Fixed standardized temporal network
Fixed between-subjects network
True means
Dataset split per person
String indicating the id variable
Vector of strings indicating the variables
Number of time points per subject
Number of variables
Number of subjects
Proportion of positive edges
Range of partial contemporaneous correlation coefficients
Range of temporal coefficients
Range of partial between-subjects coefficients
Rewiring probability of contemporaneous networks
Between-subjects variabce
Contemporaneous variance
Specifies the temporal network. Setting this to 2 connects X_i to X_(i+2)
Sacha Epskamp <mail@sachaepskamp.com>