simuMSARX: Simulate Markov-switching ARX process

In roga11/MSTest: Hypothesis Testing for Markov Switching Models

Simulate Markov-switching ARX process

Description

This function simulates a Markov-switching autoregressive process.

Usage

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.

Value

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)

roga11/MSTest documentation built on Feb. 25, 2025, 6:10 p.m.