[R] nlme model

From: Daniel O'Shea <dan.oshea_at_dnr.state.mn.us>
Date: Tue, 12 Jun 2007 11:27:14 -0500

I am having trouble figuring out the right form for the nlme arguments. I do have examples in Modern and Applied Statistics with S and from other sources, but I still can't figure it out.

I am trying to estimate species richness (sr) in streams across minnesota. My predictor variables are depth (d), habitat diversity (habdiv), drainage area (da) and an indicator variable representing the watershed/basins that the streams are in (bas: there are 10 watersheds). The variable explaining the greatest amount of variation appears to be da. I have used a log(da) to linearize the relationship, but an asymptotic relationship is more appropriate. I have used nls:

B<-c(.007,1,3,2,2,2,2,2,2,2,2,2,.05,.001,.8) st<-list(ad=B[1],ahabdiv=B[2],abas=B[3:12],b=B[13],c=B[14],z=B[15]) modnls.a<-nls(sr~ad*log(d)+ahabdiv*habdiv+abas[bas]+(b/(c+(da^-z))),


I next used a random slope and intercept model using lmer from the package (lme4).


What I would like to do is use a similar model to the modlme, but use (b/(c+(da^-z))) instead of log(da). Keeping d and habdiv as fixed effects and the sr-da relationship for each basin as a random effect. For the life of me I can not figure out the proper form of nlme. Any help would be greatly appreciated.



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