Dear Minda I don't think that you need any special package in R. You can calculate AIC scores and weights just using some basic functions. Here is an example:
##these are some models you might want to evaluate a<-glm(rtsizeB~rtsizeA) b<-glm(rtsizeB~rtsizeA+mBIO1) c<-glm(rtsizeB~rtsizeA+mBIO18) d<-glm(rtsizeB~rtsizeA+mBIO12) e<-glm(rtsizeB~rtsizeA+mBIO16) ##calculate AIC values and weights for growth models A<-AIC(a,b,c,d,e) dA<- -min(A[2])+A[2] rL<-exp(-0.5*dA) ##this is the relative likelihood wAIC<- rL/sum(rL) wAIC #this is the weighted AIC score If however, you need AICc scores, you can just take advantage of the definitions given by: AIC<- -2*LL + 2*K AICc<-AIC + 2*K*(K+1)/(n-K-1) where LL is the logLik(), K is the the number of parameters in the fitted model, and n is the number of observation, so if you know AIC then it is easy to calculate AICc. Good Luck! Kerry Cutler University of Wyoming On Wed, Oct 26, 2011 at 9:32 AM, Minda Berbeco <[email protected]> wrote: > Hello, > > I am looking for recommendations for programs to use for calculating AIC > scores. I've looked into the AICcmodavg package with R, but the associated > instructional material is not clear and I have not been able to get it to > work. I hear that SAS is good as well, but have not found a good book that > tells me how to create AIC scores (recommendations would be appreciated). > I've also looked into SPSS, which according to IBM can create AIC scores, > but have had no success. > > Any recommendations for programs and clear associated instructional > material > with information on how to run the program, write the code etc. would be > greatly appreciated. > > Thanks, > > Minda Berbeco > Viticulture and Enology, UC Davis > [email protected] >
