Dear list,
I have encountered a problem with predict.nls (Windows XP, R.2.5.0), but I am
not sure if it is a bug...
On the nls man page, an example is:
DNase1 <- subset(DNase, Run == 1)
fm2DNase1 <- nls(density ~ 1/(1 + exp((xmid - log(conc))/scal)),
data = DNase1,
start = list(xmid = 0, scal = 1))
alg = "plinear", trace = TRUE)
Now consider prediction:
> predict(fm2DNase1)
[1] 0.001424337 0.001424337 0.028883648 0.028883648 .....
> predict(fm2DNase1,newdata=fm2DNase1)
Error in if (sum(wrong) == 1) stop(gettextf("variable '%s' was fitted with
class \"%s\" but class \"%s\" was supplied", :
missing value where TRUE/FALSE needed
What causes the trouble is the call to .checkMFClasses(cl, newdata) in
predict.nls.
Incidently, on the predict.nls page the example works:
> fm <- nls(demand ~ SSasympOrig(Time, A, lrc), data = BOD)
> predict(fm)
[1] 7.887449 12.524977 15.251673 16.854870 17.797490 18.677580
> predict(fm,newdata=BOD)
[1] 7.887449 12.524977 15.251673 16.854870 17.797490 18.677580
attr(,"gradient")
A lrc
[1,] 0.4120369 5.977499
[2,] 0.6542994 7.029098
....
Is there a bug, or am I overlooking something??
Regards
Søren
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