Here are some approaches: - we only have 4 parameters so just use grid search to get starting values as in:
https://stat.ethz.ch/pipermail/r-help/2005-September/079617.html - there are singularities near beta_1 = beta_2 and near alpha_1 = 0 and near alpha_2 = 0 so reparameterize and use the upper and lower bounds to avoid those regions. You could try a separate reduced model for those. On 9/18/06, Sebastian P. Luque <[EMAIL PROTECTED]> wrote: > Hi, > > I'm trying to fit the following model to data using 'nls': > > > y = alpha_1 * beta_1 * exp(-beta_1 * x) + > alpha_2 * beta_2 * exp(-beta_2 * x) > > > and the call I've been using is: > > > nls(y ~ alpha_1 * beta_1 * exp(-beta_1 * x) + > alpha_2 * beta_2 * exp(-beta_2 * x), > start=list(alpha_1=4, alpha_2=2, beta_1=3.5, beta_2=2.5), > trace=TRUE, control=nls.control(maxiter = 200)) > > > So the model has 4 parameters (alpha_1, alpha_2, beta_1, beta_2), but > providing appropriate starting values is proving difficult. Although the > data could reasonably be fit with this model, the procedure is exiting > with "singular gradient matrix at initial parameter estimates". How can > one obtain appropriate starting values, assuming that is really the > problem? The archives show some suggestions to use 'optim', but that > requires starting values too, so I'm not sure how to proceed. > > Searching for self-starting functions, I found that there's one for a > bi-exponential model, which is very similar to the one I'm trying to fit. > Would it be reasonable to create a modified version of this function, so > that it returns a value that can be used for the model above? I would > greatly appreciate any comments and suggestions. > > > -- > Seb > > ______________________________________________ > [email protected] 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. > ______________________________________________ [email protected] 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.
