Thanks for Ben. Model selection by AIC is feasible by the code below. One more question, when is it appropriate to carry out model averaging and parameter averaging?
code library(MuMIn) data(Cement) lm1 <- lm(y ~ ., data = Cement) dd <- dredge(lm1, beta = TRUE, eval = TRUE, rank = "AIC") print(dd) Elaine On Mon, Aug 16, 2010 at 9:21 PM, Ben Bolker <bbol...@gmail.com> wrote: > elaine kuo <elaine.kuo.tw <at> gmail.com> writes: > > [re: MuMIn package] > > > However, the criteria in this package for model selection are AICc > > (second-order AIC) and QAIC (quasi-AIC). > > Please kindly share if it is possible to carry AIC rather than the > metrics > > above using this package. > > Thank you. > > I think you're misunderstanding the documentation. The reason > that AICc and QAIC are explicitly included in the package, and the > package documentation, is that (unlike AIC and BIC) they are *not* > implemented in base R. If you simply use dredge(...,rank="AIC") > that should work. > > good luck. > > ______________________________________________ > 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.
