joe, some procs in SAs calculates log likelihood differently than what it is supposed to be. try using proc nlmixed and specifying the LL explicitly. in your case, I has stronger faith in R result instead of SAS result.
On 9/26/07, Joe Yarmus <[EMAIL PROTECTED]> wrote: > In accordance with Venables and Ripley, SAS documentation and other > sources AIC with sigma^2 unknown is calculated as: > AIC = -2LL + 2* #parameters = n log(RSS/n) + 2p > For the fitness data: > (http://support.sas.com/ctx/samples/index.jsp?sid=927), SAS gets an AIC > of 64.534 with model oxygen = runtime. (SAS STAT User's Guide. Chapter > 61. pp 3956, the REG Procedure). This value of AIC accords with p = 2. > > When I run the same problem in R ver 2.5.1, I get > > > rt.glm =glm(oxy ~ runtime, data=fitness) > > rt.glm > Call: glm(formula = oxy ~ runtime, data = fitness) > > Coefficients: > (Intercept) runtime > 82.422 -3.311 > > Degrees of Freedom: 30 Total (i.e. Null); 29 Residual > Null Deviance: 851.4 > Residual Deviance: 218.5 AIC: 154.5 > > I get very close to what R gets if the constant term is included in > -2LL, (31*Log(2*pi)+n-1), divide RSS by n-1 and the number of parameters > is 3 (the predictor, the intercept and the error term) > > 31 * (log(2*pi)+log(sum(rt.glm$res^2)/30)) + 30 + 2 * 3 > [1] 154.5248 > > AIC(rt.glm) > [1] 154.5083 > > 3 questions: > 1) Why the discrepancy between SAS and R? > 2) Why the slight difference between my calculation in R and R's AIC? > 3) How should AIC be computed if row weights are used in the linear model? > > Thanks! > > -joe yarmus > > ______________________________________________ > 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. > -- =============================== "I am dying with the help of too many physicians." - Alexander the Great, on his deathbed =============================== WenSui Liu (http://spaces.msn.com/statcompute/blog) ______________________________________________ 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.
