simuNorm: Simulate normally distributed process

In roga11/MSTest: Hypothesis Testing for Markov Switching Models

Simulate normally distributed process

Description

This function simulates a normally distributed process.

Usage

simuNorm(mdl_h0, burnin = 0)

Arguments

mdl_h0

List containing the following DGP parameters n: Length of series. mu: A (q x 1) vector of means. sigma: A (q x q) covariance matrix. q: Number of series. 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 q) 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 series and its DGP parameters.

Examples

set.seed(1234)
# Define DGP 
mdl_norm <- list(n     = 1000, 
                 q     = 2,
                 mu    = c(5, -2),
                 sigma = rbind(c(5.0, 1.5),
                               c(1.5, 1.0)))

# Simulate process using simuNorm() function
y_norm_simu <- simuNorm(mdl_norm)

plot(y_norm_simu)

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