learning Vector autoregression (VAR) model parameters from multiple realizations of a stochastic process

Hi All,

I had a query regarding learning a Vector autoregression (VAR) model from multiple realizations of a stochastic process.Assume that we have many multivariate time series instances and we want to learn a single VAR model which attempts to explain them all (assumption is that all the multivariate time series instances that we have are realization of the single VAR model ). Is there any standard function that we can make use of to learn such a VAR model?.

Put differently, is it possible to learn a VAR model from multiple multivariate time series instances?

Thanks & Regards Jobin Wilson