Hi, Thank you for the reply and suggestions.
I have two questions? 1) If I want to use log, it seems that I have to take log from both sides of the model which will lead to lm(log(q)~log(-depth)). What is tehdifference between this syntax and lm(log(q) ~ I(-depth))? 2) How can I calculate the R-squared of a fitted non linear model? Regards Saeed Christian Ritz-3 wrote: > > Hi Saeed, > > one approach is to try out several initial value combinations for a and b. > > It often helps to find initial values of the same order of magnitude and > of the same sign > as the final estimates. > > To get such initial values, you could linearize the model: > > lm(log(q) ~ I(-depth)) > > > and supply the estimated coefficients from the linear regression as > starting values: > > nreg <- nls(q ~ a*exp(-b*depth), start = list(a = 0.76168, b = -0.08484)) > summary(nreg) > > > Christian > > ______________________________________________ > 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. > > -- View this message in context: http://www.nabble.com/An-error-in-fitting-a-non-linear-regression-tp22118160p22179525.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
