similar to: nls fits by groups

Hello, I'm a beginner with R and it's the first time I'm using the R-help list... I hope I'm in the right place, if not: Sorry!! I need to do non linear regressions on a data set which columns are: "river.name" "Portata" "PTG.P" "PO4.P" "NT.N" "NH4.N" "NO3.N" "BOD5" "SiO2"

Dear R-Help, I'm trying to fit a model of the following form using gnls. I've fitted it using nlsList with the following syntax: nlsList(Y~log(exp(a0-a1*X)+exp(b0-b1*X))|K,start=list (a0=6,a1=0.2,b0=4.5,b1=0.001),data=data.frame(Y=y,X=X,K=k))) which works just fine: <snip> Coefficients: a0 a1 b0 b1 1 5.459381 0.5006811 5.137458 -0.0040548687

Hi all, I'm working with a dataset from 10 treatments, each treatment with 30 subjects, each subject measured 5 times. The plot of the dataset suggests that a 3-parameter logistic could be a reasonable function to describe the data. When I try to fit the model using gnls I got the message 'Step halving factor reduced below minimum in NLS step'. I´m using as the initial values of the

Full_Name: Tadashi Kadowaki Version: 2.4.0 OS: Redhat Linux 9 Submission from: (NULL) (58.12.166.67) Doesn't nls function support subset? It seems not to work. And, there are no information in the online help. Has it sunk into oblivion?

Hello: Let me rephrase my question to attract interest in the problem I'm having. When I appply anova() to two equations estimated using glmmPQL, I get a complaint, > anova(fm1, fm2) Error in anova.lme(fm1, fm2) : Objects must inherit from classes "gls", "gnls" "lm","lmList", "lme","nlme","nlsList", or "nls"

Hello all. I was wondering if the logLike.nls() and logLike.nlme() functions are still being used. Neither function seems to be available in the most recent release of R (1.9.1). The following is contained in the help file for logLik(): "classes which already have methods for this function include: 'glm', 'lm', 'nls' and 'gls', 'lme' and others in

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

Hi all, I'm trying to fit a nonlinear (logistic-like) regression, and I'd like to get some recommendations for which package to use. The expression I want to fit is something like: y ~ A * exp(X * Beta1) / (1 + exp(-(x + X * Beta2 - xmid)/scal)) Basically, it's a logistic function, but I want to be able to modify the saturation amplitude by a few parameters (Beta1) and shift the

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 ~

Hello: Will someone PLEASE help me with this problem. This is the third time I've posted it. When I appply anova() to two equations estimated using glmmPQL, I get a complaint, > anova(fm1, fm2) Error in anova.lme(fm1, fm2) : Objects must inherit from classes "gls", "gnls" "lm","lmList", "lme","nlme","nlsList", or

Hi R-users, Could you give me some advice in solving the problem of such error message from gnls and nls? ## begin error message "Problem in gnls(y1 ~ glogit4(b, c, m, t, x), data.frame(x..: Step halving factor reduced below minimum in NLS step " ##and "Problem in nls(y ~ 1/(1 + exp((xmid - x)/scal)), data = x..: step factor reduced below minimum "? Thank you in

Hi all, I am trying to use nonlinear regression (nls) to analyze some seed germination data, but am having problems with error codes. The data that I have closely matches the germination dataset included in the drc package. Here is the head of the data temp species start end germinated TotSeeds TotGerminated Prop 1 10 wheat 0 1 0 20 0 0.0 2 10 wheat

  Hi, I fitted tree growth data with Chapman-Richards growth function using nls. summary(fit.nls) Formula: Parameters: Estimate Std. Error t value Pr Signif. codes: 0 ''***'' 0.001 ''**'' 0.01 ''*'' 0.05 ''.'' 0.1 '' '' 1 Residual standard error: 1.879 on 713 degrees of freedom Algorithm

Just thought I would share a tip I learned: The function I() is useful for specifying constants to formulas and regressions. It will prevent nls (for example) from trying to treat the variable inside I() as something it needs to estimate. An example is below. -David P.S. This may be obvious to some, but it is not made clear to be by the documentation or common books that I reviewed.

>>>>> 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

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 not such expert to see any problem with data. Seems to me, that something has to be wrong with nlsList function. > wheat.list <- nlsList(Prop ~ SSlogis(end,Asym, xmid,

Hello, I'm using the following for loop to find regression curves using a list of functions (formList), a list of starting values (startList), uppervalues (upperList) and lower values (lowerList). A sample of the list of function I use in the loop is the following: FormList <- list(PTG.P ~ fz1(Portata, a, b), PTG.P ~ fz2(Portata, a, b), PTG.P ~ fz3(Portata,a, b, d, e), PTG.P ~

I use model comparison with glms without mixed effects with anova(modelA,modelB), with mixed effects glm (glmmPQL), this doesn't work. Is there a way to compare model fits with glmmPQL's? Paula M. den Hartog Behavioural Biology Institute of Biology Leiden Leiden University [[alternative HTML version deleted]]

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 R Community, I am attempting to perform a weighted non-linear least squares fit. It has already been noted that the weights option is not yet implemented for the nls function, but no one seems to offer any suggestions for getting around this problem. I am still curious if a) anyone has code they have written which includes a weight options for nls, or b) if there is another model which