mcSimulations: Monte Carlo simulations

In svazzole/sparseVAR: Sparse VAR/VECM Models Estimation

Description

This function generates monte carlo simultaions of sparse VAR and its estimation (at the moment only for VAR(1) processes).

Usage

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)

Value

a nMcx5 matrix with the results of the Monte Carlo estimation

svazzole/sparseVAR documentation built on April 19, 2021, 2:11 p.m.