Hello Paul Thanks for the answer but my point is not how to simulate a VAR(p) process and check that it is stable. My question is more how can I generate a VAR(p) such that I already know that it is stable.
We know a condition that assure that it is stable (see first message) but this is not a condition on coefficients etc... What I want is generate say a 1000 random VAR(3) processes over say 500 time periods that will be STABLE (meaning If I run stability() all will pass the test) When I try to do that it seems that none of the VAR I am generating pass this test, so I assume that the class of stable VAR(p) is very small compared to the whole VAR(p) process. -- View this message in context: http://r.789695.n4.nabble.com/simulating-stable-VAR-process-tp4261177p4291835.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.
