mcSimulations function

Monte Carlo simulations

This function generates Monte Carlo simulations of sparse VAR and its estimation (at the moment only for VAR(1) processes).

mcSimulations(
  N,
  nobs = 250,
  nMC = 100,
  rho = 0.5,
  sparsity = 0.05,
  penalty = "ENET",
  covariance = "Toeplitz",
  method = "normal",
  modelSel = "cv",
  ...
)

Arguments

• N: dimension of the multivariate time series.
• nobs: number of observations to be generated.
• nMC: number of Monte Carlo simulations.
• rho: base value for the covariance.
• sparsity: density of non zero entries of the VAR matrices.
• penalty: penalty function to use for LS estimation. Possible values are "ENET", "SCAD" or "MCP".
• covariance: type of covariance matrix to be used in the generation of the sparse VAR model.
• method: which type of distribution to use in the generation of the entries of the matrices.
• modelSel: select which model selection criteria to use ("cv" or "timeslice").
• ...: (TODO: complete)

Returns

a nMcx5 matrix with the results of the Monte Carlo estimation