On Jan 23, 2008 3:44 PM, Jarek Jasiewicz <[EMAIL PROTECTED]> wrote: > Gabor Grothendieck wrote: > > Try port algorithm. Please provide complete reproducible code and data > > when posting. > > > > > >> y <- 1/(x <- 1:5) > >> nls(y~k/x^n, start=list(k=1, n=1), algorithm = "port") > >> > > Nonlinear regression model > > model: y ~ k/x^n > > data: parent.frame() > > k n > > 1 1 > > residual sum-of-squares: 0 > > > > Algorithm "port", convergence message: both X-convergence and relative > > convergence (5) > > > > > > > thanks, but unfortunaltly not work > > here data and problem: > > tmp=data.frame(t=c(0,40,100,330,950,15200), > h=c(0.362,0.278,0.218,0.169,0.139,0.024)) > fm=formula(t~ tr+ (ts-tr)/ ((1+ (a*h)^n)^(1-(1/n)))) > start=list(a=0.05, n=1.5, ts=0.5, tr=0.05) > > p=nls(fm, data=tmp,start=start, algorithm = "port") > ------ > Error in numericDeriv(form[[3]], names(ind), env, ifelse(internalPars < : > Missing value or an infinity produced when evaluating the model >
This is a completely different problem! Note that: - presumably a and n > 0 but that has not been specified - the problem is singular near n = 1 which is not allowed - its linear in two parameters grid a and n and then solve the other two with lm at each iteration. That may be enough to solve it or at least get starting values which might keep it away from the problem regions. ______________________________________________ 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.
