Dear R community, I am currently fitting non-linear models using nlm and nls. 1) I would like to compare the different models analogous to the comparison of linear models with anova(). Is there a function in R which allows to do that? 2) I would like to constrain the parameter ranges to positive values only. Is there an option in nlm or nls which allows to constrain parameter ranges? (So far I constrained them "manually" by incorporating the constraints into the definition of the functions fitted.) Thanks for your help, Roland --------------------------------------------------------------------------- Roland Regoes Department of Biology Emory University 1510 Clifton Rd Atlanta, GA 30322 tel: (404) 727-1765 fax: (404) 727-2880 --------------------------------------------------------------------------- -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
Roland Regoes <rregoes at emory.edu> writes:> Dear R community, > > I am currently fitting non-linear models using nlm and nls. > > 1) I would like to compare the different models analogous to the > comparison of linear models with anova(). Is there a function in R which > allows to do that?For nls there is an anova.nls function that can be used to compare two or more models. It is in the nls package. Because nlm is a general optimization routine it would not be possible to write a model comparison function for two models fit by nlm. You would need to be more specific about what the criterion means statistically. For example, if the criterion is the log-likelihood then you can compare the fitted models via a likelihood ratio test with p-values determined from a chi-square distribution.> 2) I would like to constrain the parameter ranges to positive values > only. Is there an option in nlm or nls which allows to constrain > parameter ranges? (So far I constrained them "manually" by incorporating > the constraints into the definition of the functions fitted.)For nonlinear models I prefer to incorporate the constraints into the definition of the parameters. If a parameter such as a rate constant can only take on positive values then I do the optimization with respect to the logarithm of the rate constant. In most such cases the residual sum of squares is closer to being quadratic in the scale of the logarithm of the rate constant than in the scale of the rate constant. Your mileage may vary. If you prefer to use constraints you should try the optim function which offers a constrained optimization method. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._