Simulates an mlVAR model and data with a random variance-covariance matrix for the random effects.
mlVARsim(nPerson = 10, nNode = 5, nTime = 100, lag = 1, thetaVar = rep(1,nNode),
DF_theta = nNode * 2, mu_SD = c(1, 1), init_beta_SD = c(0.1, 1), fixedMuSD = 1,
shrink_fixed = 0.9, shrink_deviation = 0.9)
Number of subjects
Number of variables
Number of observations per person
The maximum lag to be used
Contemporaneous fixed effect variances
Degrees of freedom in simulating person-specific contemporaneous covariances (e.g., the individual differences in contemporaneous effects)
Range of standard deviation for the means
Initial range of standard deviations for the temporal effects
Standard deviation used in sampling the fixed effects
Shrinkage factor for shrinking the fixed effects if the VAR model is not stationary
Shrinkage factor for shrinking the random effects variance if the VAR model is not stationary
Sacha Epskamp (mail@sachaepskamp.com)