simuMSARX function

Simulate Markov-switching ARX process

This function simulates a Markov-switching autoregressive process.

simuMSARX(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 1) vector with mean of process in each regime.
  • sigma: A (k x 1) vector with standard deviation of process in each regime.
  • phi: Vector of autoregressive coefficients.
  • 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.
  • Z: A (T x qz) matrix with exogenous regressors (Optional) and where qz is the number of exogenous variables.
  • betaZ: A (qz x 1) matrix true coefficients on exogenous regressors (Optional) and where qz is the number of exogenous variables.

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

Returns

List with simulated Markov-switching autoregressive process and its DGP properties.

Examples

set.seed(1234)
# Define DGP of MS AR process
mdl_ms2 <- list(n     = 500, 
                mu    = c(5,10),
                sigma = c(1,2),
                phi   = c(0.5, 0.2),
                k     = 2,
                P     = rbind(c(0.90, 0.10),
                              c(0.10, 0.90)))

# Simulate process using simuMSAR() function
y_ms_simu <- simuMSAR(mdl_ms2)

plot(y_ms_simu)