Dear R-users, I am trying to create a model using the NLS function, such that:
Y = f(X) + q + e Where f is a nonlinear (Weibull: a*(1-exp(-b*X^c)) function of X and q is a covariate (continous variable) and e is an error term. I know that you can create multiple nonlinear regressions where x is polynomial for example, but is it possible to do this kind of thing when x is a function with unknown coefficients (a,b,c)? Ultimately, I am expecting the output to give individual regression models for each coefficient (a,b,c) with q as a covariate. I have tried the following code, and get the resultant error messages: > weib.nls <- nls(Y ~ (a*(1-exp(-b*X^c)))|q, > + data=DATA, > + start=c(a=75,b=0.05,c=0.7)) > Error in nlsModel(formula, mf, start, wts) : > singular gradient matrix at initial parameter estimates > > summary(weib.nls) > > weib.nls2 <- nls(Y~ (a*(1-exp(-b*X^c)))+q, > + data=DATA, > + start=c(a=75,b=0.05,c=0.7)) > Error in numericDeriv(form[[3L]], names(ind), env) : > Missing value or an infinity produced when evaluating the model > Many thanks in advance! Lindsay ______________________________________________ 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.
