Suchandra Thapa <[EMAIL PROTECTED]> writes: > I'm running into problems trying to use the nls function to fit the some > data. I'm invoking nls using > > nls(s~k/(a+r)^b, start=list(k=1, a=13, b=0.59)) > > but I get errors indicating that the step has been reduced below the > minimum step size or an inifinity is generated in numericDeriv. I've > tried to use a variety of starting values for a, b, k but get similar > errors. > > Is there anything I can do to get the a fit or is there an alternative > to the nls function?
Well, first you plot the data and see if the relationship between r and s is sufficiently well defined to estimate three parameters in a nonlinear model. It is common to try to estimate more parameters than can reasonably be determined from the data. Secondly, the parameter k is conditionally linear so you can try fitting the model as nls(s ~ 1/(a+r)^b, start = list(a = 13, b = 0.59), alg = 'plinear', trace = TRUE) I recommend using trace = TRUE on difficult problems so you can see exactly where the iterations are going. If that shows unstable behavior then try to determine how the model is collapsing. In particular, what is happening to the value of a? -- Douglas Bates [EMAIL PROTECTED] Statistics Department 608/262-2598 University of Wisconsin - Madison http://www.stat.wisc.edu/~bates/ ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
