On Sat, 12 Nov 2011, Michel Rapinski <[email protected]> wrote: >Hello, > >There is a function in R's basic library (stats), step(), which allows >step by step selection of variables (forward, backward, both) on multiple >linear regression models based on AIC scores. > >Unfortunately, and correct me if I am wrong, it only works for lm, aov and >glm models.
The package AICcmodavg handles many other types of linear models. It's on CRAN. >In the case of selecting variables for canonical analysis, >more specifically redundancy analysis (RDA), are there functions that >enables these same test on rda models? I figured that since RDA is >basically a multivariate extension of the multiple linear regression, it >should work, but no luck! There are important differences between ordination and linear models. Beyond that, the issue of selecting important variables is far more complex than just an automated routine to search through them for "significance" (of any kind). Patrick's recommendation to have a look at the book by Burnham and Anderson is a good one -- start with pp 84-85 and section 4.4 (pp 167 ->). >I have succesfully managed to use the forward.sel() function in >library(packfor), for selecting variables in my multivariate RDA models, >but I also wish to do backward and alternating selection to help in the >selection of my variables. > >Help will be greatly appreciated. > >Michel > >Michel Rapinski, MSc. Student >Inst. of Plant Biology Research, Montreal Botanical Garden >Université de Montréal >Montréal, QC H1X 2B2 >Tel: 514.772-1710 >Fax: 514.872.9406 >[email protected] >University of Ottawa >[email protected] > >> Hi Minda, >> >> AIC scores depend upon the statistical models used. I think R does the >> best job of providing these scores, for example in the context of multiple >> linear regression and generalized linear models. >> >> The literature on R or on stats using R is growing rapidly. You will find >> readable treatments of AIC in Crawley's 2007 R book or in Zuur et >> al'sv2009 Mixed Effects Models and extensions in Ecology with R. >> >> And do not forget to examine ( I am not sure read is a realistic option) >> the valuable book by Burnham and Anderson 2002, Models Selection and >> Multimodel Inference. >> >> >> Patrick Foley >> bees, fleas, flowers, disease >> [email protected] >> ________________________________________ >> From: Minda Berbeco [[email protected]] >> Sent: Wednesday, October 26, 2011 8:32 AM >> To: [email protected] >> Subject: [ECOLOG-L] AIC scores >> >> 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] >>
