On 12-07-11 2:34 PM, Jonas Stein wrote:
Take a look at the predicted values at your starting fit: there's a
discontinuity at 0.4, which sure makes it look as though overflow is
occurring. I'd recommend expanding tanh() in terms of exponentials and
rewrite the prediction in a way that won't overflow.
Duncan Murdoch
Hi Duncan,
Thank you for your suggestion. I wrote a function "mytanh" and
nls terminates a bit later with another error message:
Error in nls(data = dd, y ~ 1/2 * (1 - mytanh((x - ttt)/1e-04) * exp(-x/tau2)),
:
number of iterations exceeded maximum of 50
How can i fix that?
Kind regards,
Jonas
============================ R CODE STARTS HERE =======
mytanh<- function(x){
return(x - x^3/3 + 2*x^5 /15 - 17 * x^7/315)
}
That looks like it would overflow as soon as abs(x-ttt) got large, just
like the original. You might be able to fix it by following the advice
I gave last time, or maybe you need to rescale the parameters. In most
cases optimizers work best when the uncertainty in the parameters is all
on the same scale, typically around 1.
Duncan Murdoch
t<- seq(0,1,0.001)
t0<- 0.5
tau1<- 0.02
yy<- 1/2 * ( 1- tanh((t - t0)/0.0001) * exp(-t / tau1) ) +
rnorm(length(t))*0.001
plot(x=t, y=yy, pch=18)
dd<- data.frame(y=yy, x=t)
nlsfit<- nls(data=dd, y ~ 1/2 * ( 1- mytanh((x - ttt)/0.0001) * exp(-x /
tau2) ), start=list(ttt=0.5, tau2=0.02) , trace=TRUE)
============================ R CODE ENDS HERE =======
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