simulateVAR function

VAR simulation

This function generates a simulated multivariate VAR time series.

simulateVAR(N, p, nobs, rho, sparsity, mu, method, covariance, ...)

Arguments

• N: dimension of the time series.
• p: number of lags of the VAR model.
• nobs: number of observations to be generated.
• rho: base value for the covariance matrix.
• sparsity: density (in percentage) of the number of nonzero elements of the VAR matrices.
• mu: a vector containing the mean of the simulated process.
• method: which method to use to generate the VAR matrix. Possible values are "normal" or "bimodal".
• covariance: type of covariance matrix to use in the simulation. Possible values: "toeplitz", "block1", "block2" or simply "diagonal".
• ...: the options for the simulation. These are: muMat: the mean of the entries of the VAR matrices; sdMat: the sd of the entries of the matrices;

Returns

A a list of NxN matrices ordered by lag

data a list with two elements: series the multivariate time series and noises the time series of errors

S the variance/covariance matrix of the process