VAR {MTS} | R Documentation |
Vector Autoregressive Model
Description
Perform least squares estimation of a VAR model
Usage
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.
Value
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 |
Author(s)
Ruey S. Tsay
References
Tsay (2014, Chapter 3). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.
See Also
refVAR command
Examples
data("mts-examples",package="MTS")
gdp=log(qgdp[,3:5])
zt=diffM(gdp)
m1=VAR(zt,p=2)