[R] nls problem: singular gradient

[Jonas Stein]

On 07/12/2012 01:39 AM, Duncan Murdoch wrote:
> 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.

I am not shure what you mean with "rescale paramaeters", but i changed 
ttt and tau2 to 1 but nls still fails. Do you mean i can only use 
functions with tau2 and ttt close to 1?

Is there a better fit function then nls for R? Even "origin" can find 
the parameters without any problems.

nlsfit <- nls(data=dd,  y ~  1/2 * ( 1- mytanh((x - ttt)/0.0001) * 
exp(-x / tau2) ), start=list(ttt=1, tau2=1) , trace=TRUE, control = 
list(maxiter = 100))



-- 
Jonas Stein <news at jonasstein.de>