VAR function

Vector Autoregressive Model

Perform least squares estimation of a VAR model

VAR(x, p = 1, output = T, include.mean = T, fixed = NULL)

Arguments

• x: A T-by-k matrix of k-dimensional time series
• p: Order of VAR model. Default is 1.
• output: A logical switch to control output. Default is with output.
• include.mean: A logical switch. It is true if mean vector is estimated.
• fixed: A logical matrix used in constrained estimation. It is used mainly in model simplification, e.g., removing insignificant estimates.

Details

To remove insignificant estimates, one specifies a threshold for individual t-ratio. The fixed matrix is then defined automatically to identify those parameters for removal.

Returns

• data: Observed data

• cnst: A logical switch to include the mean constant vector

• order: VAR order

• coef: Coefficient matrix

• aic,bic,hq: Information criteria of the fitted model

• residuals: Residuals

• secoef: Standard errors of the coefficients to be used in model refinement

• Sigma: Residual covariance matrix

• Phi: AR coefficient polynomial

• Ph0: The constant vector

References

Tsay (2014, Chapter 3). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.

Author(s)

Ruey S. Tsay

See Also

refVAR command

Examples

data("mts-examples",package="MTS")
gdp=log(qgdp[,3:5])
zt=diffM(gdp)
m1=VAR(zt,p=2)