I have some longitudinal data I'm fitting with an asymptotic growth function
constrained to the origin. Visual inspection of the dataset suggests this is
reasonable!
> library(nlme)
> results <- groupedData(y~Days | ID, data=results)
> m1 <- nlsList(SSasympOrig, na.omit(results))
> m1
Call:
Model: y ~ SSasympOrig(Days, Asym, lrc) | ID
Data: na.omit(results)
Coefficients:
Asym lrc
176 5.259815 -5.048464
186 13.833871 -4.337267
300 16.007862 -4.783315
159 21.509863 -4.241172
144 103.505322 -7.040130
161 49.746946 -5.682995
170 50.964702 -5.739456
293 63.060652 -5.928408
142 49.851672 -4.707905
261 48.612882 -4.568154
184 63.633909 -5.361407
162 49.478622 -4.088146
202 714.579639 -9.128026
303 53.688201 -3.750039
275 63.298936 -4.757936
264 60.868979 -5.029757
199 64.776418 -5.163388
1368 107.784023 -6.478387
212 99.200012 -6.566332
204 67.462536 -4.994269
177 120.435299 -6.125227
92 125.594800 -6.699715
210 63.899406 -4.055854
268 68.053434 -4.037159
201 133.915623 -6.786009
255 78.692978 -4.262876
273 80.826720 -4.481234
249 90.353950 -4.188984
238 97.372830 -3.969175
248 84.202629 -3.894503
208 104.325471 -4.209675
258 265.856493 -5.741356
So this appears to work reasonably well. For theoretical reasons in this context
I also want to look at an asymptotic growth function additionally constrained
with asymptote a constant (=100), i.e. with only the rate-constant/half-life
free. I'm not sure how to modify the built-in SSasympOrig function to
achieve this however thought this would work:
> m2 <- nlsList(y~100*(1-exp(-exp(lrc*Days))), start=list(lrc=-5),
data=na.omit(results))
but this results in the error message
Error in nlsModel(formula, mf, start, wts) :
singular gradient matrix at initial parameter estimates
for every estimation
I realise that constraining the asymptote will force large changes in the
estimate of lrc (e.g. particularly in the first case ID == 176) but many of the
free-floating estimates of Asym are of the order of ~ 100 so I'm not sure
why the constrained nls model doesn't converge on at least some occasions?
Am I doing something else wrong?
Thanks
Rob