[R] Logistic regression

[Guillaume Brutel]

>
> >/ I am trying to fit a non linear regression model to time series data.
> />/ 
> />/ If I do this:
> />/ reg.logis = nls(myVar~SSlogis(myTime,Asym,xmid,scal))
> />/ I get this error message (translated to English from French):
> />/ Erreur in nls(y ~ 1/(1 + exp((xmid - x)/scal)), data = xy, start = 
> />/ list(xmid = aux[1],  :
> />/   le pas 0.000488281 became inferior to 'minFactor' of 0.000976562
> /
> If it occurs after a few iterations (was it verbose=TRUE; sorry, no docs at
> hand), almost always means that there is no unique solution. Are you sure that
> your data  level out at 1? Or is a normalization factor needed? Try to repost
> with the original data set if possible. This error message might also turn up
> when the start values were totally off, so try to plot the curve and the data
> with the start values.
>
> Setting minFactor never helped for me in that case.
>
> Dieter
Here is the original dataset I am working on:

 > myTime
Time Series:
Start = 0
End = 1066
Frequency = 0.0769230769230769
 [1]    0   13   26   39   52   65   78   91  104  117  130  143  156  
169  182
[16]  195  208  221  234  247  260  273  286  299  312  325  338  351  
364  377
[31]  390  403  416  429  442  455  468  481  494  507  520  533  546  
559  572
[46]  585  598  611  624  637  650  663  676  689  702  715  728  741  
754  767
[61]  780  793  806  819  832  845  858  871  884  897  910  923  936  
949  962
[76]  975  988 1001 1014 1027 1040 1053 1066
 >
 > myVar
Time Series:
Start = 0
End = 1066
Frequency = 0.0769230769230769
 [1]  59.88812  60.32571  60.76331  61.20090  61.63849  58.63085  59.25744
 [8]  71.99815  54.14649  25.11732  52.28806  47.93601  38.20542  43.55031
[15] 101.35488  90.63455  79.91422  69.19390  58.47357  41.52232  48.24774
[22]  31.24054  32.98928  35.33158  15.96929  17.73995  19.65816  21.57638
[29]  23.49459  26.14397  28.92629  31.70861  35.75325  46.74069  57.72812
[36]  69.56075  41.51180  27.91007  41.16375  51.24584  60.75127  70.25670
[43]  27.28310  28.82234  30.36158  31.90082  33.44006  34.97930  36.51854
[50]  75.18015  39.08242  53.25049  21.68338  21.72782  24.50556  29.30659
[57]  27.59313  23.92532  20.25751  16.30756  49.36701  87.93636  32.38620
[64]  28.05113  23.89006  27.63523  24.84287  23.81066  35.87769  24.84182
[71]  28.53371  19.53002  13.27322  15.30672  17.34021  29.75360  19.13744
[78]  29.09236  27.75517  26.52083  19.98650  26.09178  54.22785
 >