Re: large Residual in lsqnonlin

Thanks for your suggestions, John. I'll certainly try using weighted
least squares. Estimation of 5 or more parameters using only one ODE
probably does take a lot of iterations and cpu time.

I face another technical difficulty is that Line-search method does
not handle bound constraints, so if I include lower bound for my
parameters, it switches to large-scale method instead.

John D'Errico wrote:
>
>
> In article <ef1e7c1.0@xxxxxxxxxxxxxxxx>, Beiyan
<beiyanou@xxxxxxx>
> wrote:
>
>> After I changed maxIter to 200, and MaxFunEvals to 2000, the
> program
>> stopped saying:
>> No improvement in search direction: Terminating
>>
>> Any suggestions?
>
> Its very difficult to guess what can be done to
> help here. One possibility is to consider a
> weighted least squares. Simply choose weights
> by which to scale your residuals. This can be
> appropriate if the uncertainty in your model
> increases with residual size. Such proportional
> error is often appropriate.
>
> HTH,
> John D'Errico
>
>
> --
> The best material model of a cat is another, or preferably the
> same, cat.
> A. Rosenblueth, Philosophy of Science, 1945
>
> Those who can't laugh at themselves leave the job to others.
> Anonymous
>
.

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