Dear all, I am trying to fit a non linear regression model to time series data.
If I do this: reg.logis = nls(myVar~SSlogis(myTime,Asym,xmid,scal)) I get this error message (translated to English from French): Erreur in nls(y ~ 1/(1 + exp((xmid - x)/scal)), data = xy, start = list(xmid = aux[1], : le pas 0.000488281 became inferior to 'minFactor' of 0.000976562 I then tried to set the 'minFactor' value like this: reg.logis = nls(myVar~SSlogis(myTime,Asym,xmid,scal),control=nls.control(minFactor=0.000488281)) But I have exactly the same error message, so it seems that the control was not changed If I set some values for the SSlogis function like this: reg.logis=nls(myVar~SSlogis(myTime,Asym=25,xmid=600,scal=13)) or like this: reg.logis=nls(myVar~SSlogis(myTime,Asym=25,xmid=600,scal=13),control=nls.control(minFactor=0.000488281)) I still have the same error message. I have also tried with setting the starting value like this: reg.logis=nls(myVar~SSlogis(myTime,Asym=25,xmid=600,scal=13),control=nls.control(minFactor=0.000488281) + ,start=list(xmid=0,scal=13)) Bu then, I get this error message: Error in nlsModel(formula, mf, start, wts) : singular gradient matrix at initial parameter estimates Could someone tell me what I am doing wrong? Many thanks Guillaume. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
