I don't know FPE is but in the case of the Akiaike Information Criterion, the actual value depends on whether you include constants and multipliers in ( derivation of ) the formula. It doesn't matter in that case because you're only comparing AIC's ( and the lower the better ).
Since, I don't what FPE is, I can't say but maybe it's the same issue there, namely that only comparisons matter so it doesn't matter what you use. Mark On Fri, Mar 30, 2012 at 9:22 AM, jp611 <the_usua...@hotmail.com> wrote: > Hello, > > first of all I have found lots of different versions of the FPE which have > given me different results. I was wondering if there was an explicit > command > in R to compute the FPE of a model. Thank you in advance, > > Jonny > > -- > View this message in context: > http://r.789695.n4.nabble.com/Akaike-s-Final-Prediction-Error-FPE-tp4519011p4519011.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. > [[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.
