[R] nls - convergence problem
    peter.schlattmann@t-online.de 
    peter.schlattmann at t-online.de
       
    Thu Jan  6 16:27:48 CET 2005
    
    
  
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.
What can I do to deal with this problem?
Any help is appreciated!
Many thanks
peter
    
    
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