simuNorm function

Simulate normally distributed process

This function simulates a normally distributed process.

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.

Returns

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)