simulateVAR {sparsevar}

VAR simulation

Description

This function generates a simulated multivariate VAR time series.

Usage

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;

Value

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