Hello,
I am currently testing a Vector AR of dim 3 over not a lot of data (135 * 3 observations) . To test the adequation of my vecot ar, I use the Schwarz Bayesian Criterion and the classic modified Portmanteau test on the residuals (it can be found for instance in http://www.iue.it/PUB/ECO2004-8.pdf , page 15) -> the null hypothesis is "the residuals process are a vectorila white noise process with covariance matrix the one obtained from model calibration". I use the mAr package. My question is more statistical than purely r - related: If my order p is, say, 12, what lag should I use in my portmanteau test? What is usually done in practice? And are there other tests that can be performed to judge the adequation of the model? Many thanks
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