Check VAR(p) Coefficients for Stationarity

The function checks if all the eigenvalues have moduli (absolute values) less than 1. If all eigenvalues have moduli less than 1, it indicates that the VAR process is stable and, therefore, stationary. If any eigenvalue has a modulus greater than or equal to 1, it indicates that the VAR process is not stable and, therefore, non-stationary.

Usage

CheckVARCoef(coef)

Arguments

coef

Numeric matrix. Coefficient matrix with dimensions k by (k * p). Each k by k block corresponds to the coefficient matrix for a particular lag.

See also

Other Simulation of Autoregressive Data Functions: CheckARCoef(), SimARCoef(), SimAR(), SimMVN(), SimPD(), SimVARCoef(), SimVARExo(), SimVARZIPExo(), SimVARZIP(), SimVAR(), SimVariance(), YXExo(), YX()

Author

Ivan Jacob Agaloos Pesigan

Examples

set.seed(42)
(coef <- SimVARCoef(k = 3, p = 2))
#>            [,1]        [,2]      [,3]       [,4]       [,5]       [,6]
#> [1,] -0.8299143 -0.59172421 0.3160931  0.1196792 -0.4116841 -0.4670195
#> [2,]  0.4478317 -0.43004167 0.8690710  0.6294415  0.5906853 -0.8226202
#> [3,]  0.3190983  0.02594328 0.4671797 -0.5589469  0.3477687 -0.6471376
CheckVARCoef(coef = coef)
#> [1] TRUE