Thanks, it was actually p.249, at least in my MASS3. but that solved my doubt.
I've have another doubt, can this factor interact with one of the parameters in the model? My problem is basically a Michaelis Menten term, where this factor determines a different Km. The rest of the parameters in the model are the same. But I don't know how to write the nls formula, or if it is possible. This is a toy example, B and A are the two "factors", conc is the concentration and t is the temperature: ## Generate independent variables Bconc<-runif(30,0.1,10) Aconc<-runif(30,0.1,10) At<-runif(30,1,30) Bt<-runif(30,1,30) ## These are the parameters I want to calculate from ## my real data BKm<-1 AKm<-0 EBoth<--0.41 # These are my simulated dependent variables yB<-100*exp(EBoth*Bt)*Bconc/(BKm+Bconc)+rnorm(30,0,1) yA<-75*exp(EBoth*At)*Aconc/(AKm+Aconc)+rnorm(30,0,1) #The separate models BModel<-nls(Response~lev*exp(Ev*t)*conc/(Km+conc),data=list(Response=yB,t=Bt,conc=Bconc),start=list(lev=90,Ev=-0.5,Km=0.8),trace=TRUE) AModel<-nls(Response~lev*exp(Ev*t)*conc/(Km+conc),data=list(Response=yA,t=At,conc=Aconc),start=list(lev=90,Ev=-0.5,Km=0.8),trace=TRUE) ## I want to obtain a combined model of the form: ## Y=Intercept[1:2]*exp(Eboth*t)*conc/(Km[1:2]+conc) ## where I have a common E but two intercepts and two ## Kms (one of them should in fact be zero) yBoth<-c(yB,yA) concBoth<-c(Bconc,Aconc) tBoth<-c(At,Bt) AorB<-as.factor(c(rep(0,length(yA)),rep(1,length(yB)))) ## Amongst other things I've tried FullModel<-nls(Response~lev[AorB]*exp(Ev*t)*conc/(Km[AorB]+conc),data=list(Response=yBoth,t=tBoth,conc=concBoth),start=list(lev=c(90,70),Ev=-0.5,Km=c(0.8,0)),trace=TRUE) ## but i get to a singular gradient Any other pointers, thanks Manuel --- Prof Brian Ripley <[EMAIL PROTECTED]> escribió: > On Thu, 20 Apr 2006, Manuel Gutierrez wrote: > > > Is it possible to include a factor in an nls > formula? > > Yes. What do you intend by it? If you mean what it > would mean for a lm > formula, you need A[a] and starting values for A. > > There's an example on p.219 of MASS4. > > > I've searched the help pages without any luck so I > > guess it is not feasible. > > I've given it a few attempts without luck getting > the > > message: > > + not meaningful for factors in: > > Ops.factor(independ^EE, a) > > > > This is a toy example, my realworld case is much > more > > complicated (and can not be solved linearizing an > > using lm) > > a<-as.factor(c(rep(1,50),rep(0,50))) > > independ<-rnorm(100) > > respo<-rep(NA,100) > > respo[a==1]<-(independ[a==1]^2.3)+2 > > respo[a==0]<-(independ[a==0]^2.1)+3 > > > nls(respo~independ^EE+a,start=list(EE=1.8),trace=TRUE) > > > > Any pointers welcomed > > Many Thanks, > > Manu > > > > ______________________________________________ > > [email protected] mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > > > -- > Brian D. Ripley, > [EMAIL PROTECTED] > Professor of Applied Statistics, > http://www.stats.ox.ac.uk/~ripley/ > University of Oxford, Tel: +44 1865 > 272861 (self) > 1 South Parks Road, +44 1865 > 272866 (PA) > Oxford OX1 3TG, UK Fax: +44 1865 > 272595 > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
