Hi Niner <[EMAIL PROTECTED]> napsal dne 01.10.2007 18:37:17:
> Thank you very much, Petr. I define my model based on same experiment data. > The trend of (A,B) and the relationship with ev are assumed as > > 1/A = a + b*ev + c*ev^2 > 1/B = d + e*exp(f*ev) > > Both (1/A) and (1/B) are supposed to decrease (nonlinearly) with increasing > ev. The initial values I used are computed based on above equations. I knew > that the data is quite noisy. My purpose is to use the model such that when > given an interested ev, a curve of (N,CSR) can be built. > > Is it possible to force R to find (a,b,c,d,e,f,g) based on my equations? Or, > is there any other way I can do to improve the model? Thank you very much for your help. As I said I am not an expert in nonlinear modelling, but your data do not follow your expectation. > > BTW, when I ran your codes in R, I got several errors like Yes. It is an error when computing partial corelations in some groups. As far as some groups are computed you can use otput from nlsList as a starting point for nlme optimisation. For more complex explanation see Pinheiro&Bates, Mixed effects models with S and S+. > "Error in sum(rr[-(1:npar)]^2) : subscript out of bounds" > "Error in nls(formula = formula, data = data, start = start, control = control) : > singular gradient " > "Error in nls(formula = formula, data = data, start = start, control = control) : > number of iterations exceeded maximum of 50 " > "Error in nlsModel(formula, mf, start, wts) : > singular gradient matrix at initial parameter estimates " > > But the plot is OK. I don't if these errors matters. Thanks again for your > response. Hope someone can help me to find a solution to my problem. Not sure as random effects for A and B shall follouw your above mentioned relationships which they definitely dont. However maybe I am mistaken and somebody with better insight will correct me. I too would like to get opinion from experts. Regards Petr > > Niner > ---------------------------------------------------- > Niner, Seattle > [EMAIL PROTECTED] > > On Oct 1, 2007, at 1:33 AM, Petr PIKAL wrote: > > Althoug I am not an expert in nonlinear regression, it seems to me that > your data are quite noisy. I presume you have got your model from > elsewhere and now you try to use it for your data. Looking at it and using > nlme I suppose you will not get such definite model based on your data. > > Try > > data1$ev <- ordered(data1$ev) > data1.gr <- groupedData(N~CSR|ev, data1) > out <- nlsList(N~CSR/(A+B*CSR), data1.gr, start= c(A=1, B=1)) > out1<- nlme(out) > ranef(out1) > A B > 0.2 8.667265e-05 -6.267700e-04 > 0.3 -3.139092e-04 2.206547e-03 > 0.4 4.044455e-06 -2.349364e-05 > <snip> > > 3.6 -7.402470e-08 -5.312590e-06 > 5 -3.844779e-06 2.942158e-05 > > plot(as.numeric(row.names(ranef(out1))), ranef(out1)[,1]) > plot(as.numeric(row.names(ranef(out1))), ranef(out1)[,2]) > > You can clearly see that A and B random efect values are oscilating around > 0 with increasing "ev" which seems to me that A and B are independent on > ev > > Regards > Petr > [EMAIL PROTECTED] > > [EMAIL PROTECTED] napsal dne 01.10.2007 02:37:52: > > Hi, I am new to R. I don't have strong background of statistics. I am > a student of Geotechnical Engineering. I tried to run a nonlinear > regression for a three-variable function, that is > > N = f(CSR, ev) # N is a function of CSR and ev, and N = CSR/(A > +B*CSR), wherer (A,B) are function of ev. > > N, CSR and ev are observed in the experiments. > Following is my R script. > > rm(list=ls()) > library(nlme) > > # assign data > N <- c > (30.03,16.62,10.88,36.47,20.24,38.17,36.47,34.80,19.00,32.37,14.40,35.63 > > , > 19.00,17.79,33.98,31.58,31.58,35.63,20.24,31.58,29.27,22.18,27.77,25.60, > > 19.00,7.05,34.80,29.27,29.27,17.79,10.42,31.58,17.79,17.20,11.36,19.00,2 > > 9.27,12.33,22.18,22.18,14.40,31.58,19.00,9.52,33.17,13.87,19.00,21.52,11 > > .36,22.84,9.96,6.68,20.88,9.96,11.84,20.24,19.61,17.20,17.20) > > CSR <- c > (0.25,0.42,0.12,0.438,0.49,0.42,0.47,0.46,0.24,0.45,0.37,0.46,0.337,0.36 > > , > 0.334,0.346,0.399,0.44,0.246,0.33,0.413,0.23,0.45,0.45,0.44,0.106,0.333, > > 0.256,0.345,0.44,0.153,0.348,0.23,0.25,0.122,0.183,0.201,0.128,0.23,0.24 > > , > 0.129,0.438,0.228,0.111,0.409,0.14,0.24,0.20,0.22,0.22,0.152,0.094,0.131 > > ,0.123,0.155,0.28,0.204,0.149,0.193) > > ev <- c > (0.2,0.3,0.4,0.5,0.5,0.5,0.6,0.6,0.8,1,1.0,1.0,1.1,1.1,1.2,1.2,1.2,1.2,1 > > . > 3,1.3,1.3,1.3,1.3,1.3,1.4,1.5,1.5,1.5,1.5,1.5,1.6,1.6,1.6,1.6,1.7,1.7,1. > > 7,1.7,1.7,1.7,1.8,1.8,1.9,1.9,1.9,1.9,1.9,2.0,2.1,2.1,2.3,2.4,2.4,2.7,2. > > 8,3.3,3.4,3.6,5.0) > > # set the data frame > data1<- data.frame(cbind(N,CSR,ev)) > # the initial values of parameters > para1.st <- c(a=75.4,b=165.9,c=-22.4,d=0,e=0.8,f=-0.28,g=0) > para2.st <- c(a=31.3,b=-176.9,c=53.41,d=0,e=75.2,f=-0.18,g=0) > # call nls funciton > try.control <- c(maxiter=100, minFactor=1/4096) > out <- nls(N~CSR/(1/(a+b*ev+c*(ev^2))+CSR/(d+e*exp(f*ev)))-g, data1, > start=para1.st, control=try.control, trace=T) > > The data is from experiments and the pattern of data is scatter quite > a bit. I want to find the best fit coefficients (a,b,c,d,e,f,g) for > the data. > I have two different sets of initial values for try. But in both > cases I got error message of > "singular gradint" > > What can I do for this error? Is there any other nonlinear regression > model I can try? This problem is kind of emergency. I really hope > someone can help me out. Any comment is appreciated. Thanks a lot. > > Niner > ----------------------------------------------- > Yi-Min Huang > Civil & Environmental Engineering > U. of Washington > 206-6165697 > > ---------------------------------------------------- > Niner, Seattle > [EMAIL PROTECTED] > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. > > ______________________________________________ > 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. ______________________________________________ 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.
