Goodness to fit can be checked on looking at the PACF and/or ACF of estimated residuals. Also you might want to see how valid the normality assumption is on them.
Generally joint normality is assumed on the data, so that innovation are multivariate white noise process. Luna Moon wrote: > > Hi all, > > > I am asking this for my friend. > > > In VAR models, how do we test the goodness-of-fit of a VAR model? More > specifically in R? > > > Moreover, are there assumptions on the joint distribution of the data in > the > model? > > > Thanks a lot! > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > -- View this message in context: http://www.nabble.com/help-on-vector-auto-regressive-model-tp25099737p25100636.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
