[R] nls - convergence problem
Douglas Bates
bates at wisc.edu
Fri Jan 7 17:22:36 CET 2005
peter.schlattmann at t-online.de wrote:
> Dear list,
>
> I do have a problem with nls. I use the following data:
>
>
>>test
>
> time conc dose
> 0.50 5.40 1
> 0.75 11.10 1
> 1.00 8.40 1
> 1.25 13.80 1
> 1.50 15.50 1
> 1.75 18.00 1
> 2.00 17.00 1
> 2.50 13.90 1
> 3.00 11.20 1
> 3.50 9.90 1
> 4.00 4.70 1
> 5.00 5.00 1
> 6.00 1.90 1
> 7.00 1.90 1
> 9.00 1.10 1
> 12.00 0.95 1
> 14.00 0.46 1
> 24.00 NA 1
> 30.00 NA 1
> 36.00 NA 1
>
> I use the self-starting function SSfol:
>
> nls(conc~SSfol(dose,time,lKe,lKa,lCl),data=test,trace=T,control=nls.control(maxiter=13,tol=0.001,minFactor=1.E-500),na.action=na.omit)
>
> This gives the following output:
>
> 99.15824 : -1.2061792 0.1296157 -4.3020997
> 86.07567 : -0.7053265 -0.3873204 -4.1278009
> 85.19743 : -0.5548499 -0.5333776 -4.1173627
> 85.19246 : -0.5466376 -0.5415731 -4.1173247
> 85.1922 : -0.5444637 -0.5437461 -4.1173223
> 85.1922 : -0.5442240 -0.5439857 -4.1173223
> 85.1922 : -0.5441337 -0.5440760 -4.1173223
> 85.1922 : -0.5441104 -0.5440993 -4.1173223
> 85.1922 : -0.5440984 -0.5441113 -4.1173223
> 85.1922 : -0.5441089 -0.5441008 -4.1173223
> 85.1922 : -0.5441006 -0.5441091 -4.1173223
> 85.1922 : -0.5441051 -0.5441046 -4.1173223
> 85.1922 : -0.5441051 -0.5441046 -4.1173223
> 85.1922 : -0.5441051 -0.5441046 -4.1173223
>
> Error in nls(conc ~ SSfol(dose, time, lKe, lKa, lCl), data = test, trace
> = T, :
> number of iterations exceeded maximum of 13
>
> I do not understand this error message for two reasons:
>
> 1. Apparently the algorithm has converged, at the end of the output the
> change of parameter estimates seems to be less than 0.001
>
>
> 2. If the maximum number of iterations is reached I would expect a
> warning in the case that the algortihm did not converge. However, here
> the algorithm apparently has converged. Thus I do not understand what
> happened.
But it hasn't converged. The nls function uses a relative offset
convergence criterion that is not being satisfied here. By setting the
minimum step factor to a very small number you are more small steps than
you would otherwise but you are not converging. It appears that the
parameter estimates are not defined for this model/data set combination.
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