MSTest (version 0.1.5)

simuMSVAR: Simulate Markov-switching vector autoregressive process

Description

This function simulates a Markov-switching vector autoregressive process.

Usage

simuMSVAR(mdl_h0, burnin = 100)

Value

List with simulated vector autoregressive series and its DGP parameters.

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.

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)