similar to: nlsList problems: control option does not effect output and strange environment search

Howdee, My question appears at #6 below: 1. I want to model the growth of each of a large number of individuals using a 4-parameter logistic growth curve. 2. nlme does not converge with the random structure that I want to use. 3. nlsList does not converge for some individuals. 4. I decided to go around nlsList using: t(sapply(split(data, list(data$id)), function(subd){coef(nls(mass ~

Howdee, I am able to fit a 4-parameter logistic growth curve to a dataset which comprise many individuals (using R v. 2.3.1). Yet, if I want to obtain the parameters for each individual (i.e., for each 'id') using nlsList, then I obtain an Error message which I have trouble interpreting. Any advice as to how I can solve this problem? Thanks for your time, Marc > reg <-nls(mass ~

I'm trying to fit a Gompertz sigmoid as follows: x <- c(15, 16, 17, 18, 19) # arbitrary example data here; y <- c(0.1, 1.8, 2.2, 2.6, 2.9) # actual data is similar gm <- nls(y ~ a+b*exp(-exp(-c*(x-d))), start=c(a=?, b=?, c=?, d=?)) I have been unable to properly set the starting value '?'s. All of my guesses yield either a "singular gradient" error if they

Hello, nls library provides 6 self-starting models, among them: SSfp, a four parameters logistic function. Its self-starting procedure involves several steps. One of these steps is: pars <- as.vector(coef(nls(y ~ cbind(1, 1/(1 + exp((xmid - x)/exp(lscal)))), data = xydata, start = list(lscal = 0), algorithm = "plinear"))) which assumes an initial value of lscal equal to 0. If lscal

Hi All. I'd like to send some control arguments to the nls function when performing a nlsList analysis. I'm fitting a power model to some grouped data and would like to impose lower bounds on the estimates using the "port" algorithm. Obtaining the lower bound constraint works fine with a direct call to nls for a single level of the grouping variable. ?However, the bounds

Hi Rick Thanks to Dieter Menne I did manage to solve the problem of imposing bounds on the parameter space duirng an nlsList fit. He suggested using optim to optimize the parameters prior to each fit. This worked well for me as I had a customized selfStart function that then optimized the parameters for each individual separately. if you rewrote your selfStart function as: powrDpltInit <-

Hi I am using nlsList from the nlme package to estimate group specific coefficient sets to get a first impression of the structure of coefficients in relation to potential predictor variables. In some cases I got coefficients in other there are conversion problems due to bad start values I guess, resulting in typical error messages as known from nls: Error in nls(formula = formula, data = data,

When I run gnls I get the error: Error in nls(y ~ cbind(1, 1/(1 + exp((xmid - x)/exp(lscal)))), data = xy, : step factor 0.000488281 reduced below 'minFactor' of 0.000976563 My first thought was to decrease minFactor but gnlsControl does not contain minFactor nor nlsMinFactor (see below). It does however contain nlsMaxIter and nlsTol which I assume are the analogs of

Hello, I'm using the nls function and would like to increase the number of iterations. According to the documentation as well as other postings on R-help, I've tried to do this using the "control" argument: nls(y ~ SSfpl(x, A, B, xmid, scal), data=my.data, control=nls.control(maxiter=200)) but no matter how much I increase "maxiter", I get the following error

I am trying to fit the 4-parameter logistic model with SSfpl. The estimation is terminated with a message "step factor 0.000488281 reduced below 'minFactor' of 0.000976562". I tried to change the minFactor with nls.control(minFactor=yy) with no apparent success. A call of nls.control() without arguments always shows the value of 0.000976562. Also the estimation terminates as

Dear listers, I am trying to fit a model using nlsList() using alternately a SSfol() selfstart function or its developped equivalent formulae. This preliminary trial works well mydata<-groupedData(Conc~Tps|Organ,data=mydata) mymod1<-nls(Conc~SSfol(Dose,Tps,lKe,lKa,lCl),data=mydata) as well as a developped form: mymod2<-nls(Conc~Dose * exp(lKe+lKa-lCl) *

Hi All I'm analysing growth rates using a gompertz (logistic) curve and am attempting to fit parameters for all of my study birds using nlsList. I've been looking for an option in nlsList to set min and max limits for parameter values during estimation, although I have failed to find any under 'control'. Other users seem to have reported that using control in the port algorithm

Hi All. I'm trying to run nlsList an getting an error that makes no sense to me. I have accuracy and reaction time data over many trials for each person (id) When I use nlsList code that is virtually identical to the example in the doc file I get the following error. I've tried everything I could think of and can't get around it. Any ideas what I'm doing wrong? **************

Thank you Martin. If I understand correctly, OP could do wheat.list <- nlsList(Prop ~ SSfpl(end, A, B, xmid, scal), data=wlg) or add some small value to all zeroes wlg$prop < -wlg$Prop+1e-7 wheat.list <- nlsList(prop ~ SSlogis(end,Asym, xmid, scal), data=wlg) which gives fairly reasonable results. plot(augPred(wheat.list)) Am I correct? Cheers Petr > -----Original Message-----

DeaR I am trying to use a dynamically create formula with nlsList and nlme, but I cannot get the environment of the string-generated formal to work similarly to the manually entered one. Any idea? Dieter #----- library(nlme) # Pinheiro/Bates p 280 fm1Indom.lis = nlsList(conc~SSbiexp(time,A1,lrc1,A2,lrc2), data=Indometh) nlme(fm1Indom.lis,random=pdDiag(A1+lrc1+A2~1)) # works... # Simulating

I hope that the mailing list is the correct forum for the question below. I have trouble calling functions nlsList and nlme from another function. Any help would be greatly appreciated. Jens Praestgaard Human Genome Sciences Rockville MD. I have a data set v with two components, v$mixeddat and v$init. They are listed below: > v$mixeddat conc result rep sample z 11 20.00000000

Hello together, Is there a tool to test the statistical differences between parameter estimates of a nlsList fit? I fitted degradation data using the nlsList method and want to find out whether derived rate constants are significantly different from each other at the grouping factors soil and temperature. Regards Frank Scherr

Hi list, In the object returned by summary.nlsList, what's the difference between "coefficients" and "parameters"? The have the same "Estimate", different se (therefore t value), but same p values. R.2.8.0 on winxp with nlme_3.1-89 Thanks, ...Tao +++++++++++++++++++++++++++++++++++++++++++++++++ > library(nlme) > fm1 <- nlsList(uptake ~

>>>>> PIKAL Petr <petr.pikal at precheza.cz> >>>>> on Fri, 20 Oct 2017 06:33:36 +0000 writes: > Hi > Keep your messages in the list, you increase your chance to get some answer. > I changed your data to groupedData object (see below), but I did not find any problem in it. > plot(wlg) > gives reasonable picture and I am

Hello, nls-users, is it possible to pass additional parameters to the model function that are known and groupwise constant with nlsList? I could not find something like a "keep this fixed" option in the documentation and the code (my fault...?) The current workaround is to break the problem down into groups and use globals to pass the constant parameters, but it is ugly code and