simuMSVAR function

Simulate Markov-switching vector autoregressive process

This function simulates a Markov-switching vector autoregressive process.

simuMSVAR(mdl_h0, burnin = 100)

Arguments

• mdl_h0: List containing the following DGP parameters

  • n: Length of series.
  • k: Number of regimes.
  • mu: A (k x q) matrix of means.
  • sigma: List with k (q x q) covariance matrices.
  • phi: A (q x qp) matrix of autoregressive coefficients.
  • p: Number of autoregressive lags.
  • q: Number of series.
  • P: A (k x k) transition matrix (columns must sum to one).
  • eps: An optional (T+burnin x q) matrix with standard normal errors to be used. Errors will be generated if not provided.

• burnin: Number of simulated observations to remove from beginning. Default is 100.

Returns

List with simulated vector autoregressive series and its DGP parameters.

Examples

set.seed(1234)
# Define DGP of MS VAR process
mdl_msvar2 <- list(n     = 1000, 
                   p     = 1,
                   q     = 2,
                   mu    = rbind(c(5, -2),
                                 c(10, 2)),
                   sigma = list(rbind(c(5.0, 1.5),
                                      c(1.5, 1.0)),
                                rbind(c(7.0, 3.0),
                                      c(3.0, 2.0))),
                   phi   = rbind(c(0.50, 0.30),
                                 c(0.20, 0.70)),
                   k     = 2,
                   P     = rbind(c(0.90, 0.10),
                                 c(0.10, 0.90)))

# Simulate process using simuMSVAR() function
y_msvar_simu <- simuMSVAR(mdl_msvar2)

plot(y_msvar_simu)