search for: grpshrunk

...he same commands, got an error message: > growth.gnls <- gnls(lt ~ Linf*(1-exp(-K*(age-t0))), + data=growth.dat, params= Linf +K + t0 ~ 1, start=list(Linf=500,K=0.2,t0=0), + control = list(returnObject = T), corr = corAR1(form=~fish|age)) Error in "[<-.factor"(*tmp*, , value = grpShrunk[revOrderShrunk]) : Argument "i" is missing, with no default If I use nls function I can estimate the parameters: > growth.nls <- nls(lt ~ Linf*(1-exp(-K*(age-t0))), + data=growth.dat, start=list(Linf=500,K=0.2,t0=0)) > summary(growth.nls) Formula: lt ~ Linf * (1 - ex...

...------------ > nlme(Count ~ quad.PBMC.model(aL, aN, T0), + data = tissueData, + weights = varConstPower(form =~ Count), + start = list( fixed = c(rep(1000, 8), -2, -2) ), + fixed = list(T0 ~ TypeTissue-1, aL ~ 1, aN ~ 1), + random = aL + aN ~ 1|Tissue + ) Error in MEestimate(nlmeSt, grpShrunk) : Singularity in backsolve at level 0, block 1 > > --------------------------------------------- The above command clearly this doesn't work, but if I comment out the "weights = ..." line, it executes with no problem. I'd greatly appreciate any guidance on how to prope...

...ally, there a way to return an nlme object when the estimation process runs into a singular matrix? For example, can the results up to the point of an error such as "Error in solve.default(pdMatrix(a, fact = TRUE)) : system is computationally singular" or "Error in MEestimate(nlmeSt, grpShrunk) : Singularity in backsolve at level 0, block 1\n" be returned rather than only an error message being returned? Setting the "returnObject" nlme control option to TRUE seems to return an nlme object only when the maximum number of iterations is reached without meeting the convergenc...

...-0.137018044847307, 1.70105176178795, -3.07372462709182, -0.0445309584408364, 12.3518546784787, -3.22126648052618, -1.69049623029482, 0.907261039321137)) 5: .C(fit_nlme, thetaPNLS = as.double(c(as.vector(unlist(sran)), sfix)), pdFactor = as.double(pdFactor(nlmeSt$reStruct)), as.integer(unlist(rev(grpShrunk))), as.integer(unlist(Dims)), as.integer(attr(nlmeSt$reStruct, "settings"))[-(1:3)], as.double(cF), as.double(vW), as.integer(unlist(cD)), settings = as.double(pnlsSettings), additional = double(NReal * (pLen + 1)), as.integer(!is.null(correlation)), as.integer(!is.null(weights)),...

This works fine: fit42<-nls(Vfs~SSlogis(Months,Asym.Int+Asym.Group*Groupdum,xmid,scal), data=df, start=c(Asym.Int=22,Asym.Group=5,xmid=2,scal=6), na.action=na.omit) But this, identical except using gnls, doesn't converge: fit43<-gnls(Vfs~SSlogis(Months,Asym.Int+Asym.Group*Groupdum,xmid,scal), data=df, start=c(Asym.Int=22,Asym.Group=5,xmid=2,scal=6), na.action=na.omit) Error in gnls(Vfs