Let's assume you have just three observations, and x-- = 1:3 for your observations.
Predictor 1: y = x^2 Predictor 2: y = 1 if x=1 y = 4 if x=2 y = 9 if x=3 y = 0 elsewhere These predictors are obviously not the same, but will give the same Mean Squared Error for your data (whatever your observed y-values are). This should suffice as a counter example. Or did I misunderstand your question? HTH, Michael > -----Original Message----- > From: r-help-boun...@r-project.org > [mailto:r-help-boun...@r-project.org] On Behalf Of RON70 > Sent: Freitag, 18. September 2009 11:23 > To: r-help@r-project.org > Subject: [R] A stat related question > > > Can I ask a small stat. related question here? > > Suppose I have two predictors for a time series processes and > accuracy of predictor is measured from MSEs. My question is, > if two predictors give same MSE then, necessarily they have > to be identical? Can anyone provide me any counter example? > > Thanks. > -- > View this message in context: > http://www.nabble.com/A-stat-related-question-tp25505618p25505618.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. > ______________________________________________ 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.