Time Series Analysis: Forecasting and Control
Wiley
George E. P. Box, Gwilym M. Jenkins, Gregory C. Reinsel, Greta M. Ljung
Multivariate time series analysis and applications
John Wiley & Sons Ltd
William W.S. Wei
Time Series Analysis and Its Applications: With R Examples
Springer International Publishing
Robert H. Shumway, David S. Stoffer (auth.)
Section 3.4 of Lukepohl (2005), New introduction to multiple time series, Springer contains material on maximum likelihood estimation of VAR systems with multivariate normal disturbances. Practically speaking results are the same or asymptotically the same as standard VAR methods. I would recommend that you stick with the standard methods unless you have some particular analysis in mind
In R the standard VAR methodology is implemented in the vars package in R. (https://cran.r-project.org/web/packages/vars/). The vignette (https://cran.r-project.org/web/packages/vars/vignettes/vars.pdf) explains how to use this package. You may also find Christian Kleiber and Achim Zeileis (2008), Applied Econometrics with R, Springer and Bernhard Pfaff (2008) Analysis of Integrated and Cointegrated Time Series with R, Springer useful.
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