mlVARsim function

Simulates an mlVAR model and data

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)

Arguments

• nPerson: Number of subjects
• nNode: Number of variables
• nTime: Number of observations per person
• lag: The maximum lag to be used
• thetaVar: Contemporaneous fixed effect variances
• DF_theta: Degrees of freedom in simulating person-specific contemporaneous covariances (e.g., the individual differences in contemporaneous effects)
• mu_SD: Range of standard deviation for the means
• init_beta_SD: Initial range of standard deviations for the temporal effects
• fixedMuSD: Standard deviation used in sampling the fixed effects
• shrink_fixed: Shrinkage factor for shrinking the fixed effects if the VAR model is not stationary
• shrink_deviation: Shrinkage factor for shrinking the random effects variance if the VAR model is not stationary

Author(s)

Sacha Epskamp (mail@sachaepskamp.com)