Hello Giusy, in addition to Frank's suggestion you might want to specify and estimate a VECM (function ca.jo() in package urca). This object can be transformed to its level-VAR representation (function vec2var() in package vars) for which a predict-method exists (fan charts can be generated too). The advantage of this approach compared to a pure VAR-modeling (in levels or first differences, depending on the stationarity of your series in question) is, that you might capture the long-run relationship between your price series (arbitrage-condition?).
Best, Bernhard > >You may want to have a look at the vars package >Frank > >Giusy schrieb: >> Hello to everyone! >> I have a question for you..I need to predict multivariate >time series, for >> example sales of 2 products related one to the other, having >the 2 prices >> like inputs.. >> Is there in R a function to do it? I saw dse package but I >didn't find what >> a I'm looking for.. >> Could anyone help me? >> Thank you very much >> Giusy >> > >______________________________________________ >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. > ***************************************************************** Confidentiality Note: The information contained in this ...{{dropped:10}} ______________________________________________ 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.
