[Scilab-users] evaluate error on each parameter calculated with leastsq

[Claus Futtrup]

Hi Antoine

Initial message from Yohan was not sufficient to determine whether 
Interval Analysis could do it or not.

As I said in my previous answer - IntLab is for determining mathematical 
rounding errors and other errors of operation ... for example if you 
make almost division-by-zero, then you have a big gap of potentially 
correct solutions. This is what IntLab is for, robust mathematics, not 
curve fitting or analyzing measurement data.

Best regards,
Claus

On 2/21/2014 16:06, Antoine Monmayrant wrote:
> On 02/19/2014 08:55 PM, Samuel Gougeon wrote:
>> Le 19/02/2014 17:32, Claus Futtrup a écrit :
>>> Hi Yohan
>>>
>>> I see that I'm not alone wondering a bit about what you'd like to do.
>>>
>>> A mathematically solid and readily available technique to corner 
>>> mathematical rounding errors and other errors of operation is called 
>>> Interval Analysis.
>>>
>>> For matlab there's INTLAB. See:
>>> http://www.ti3.tu-harburg.de/~rump/intlab/
>>>
>>> I'm sure it could be converted to Scilab without big trouble. Maybe 
>>> I even have an old one laying around (??) somewhere ... maybe.
>> Yes indeed, here : http://www-sop.inria.fr/coprin/logiciels/Int4Sci/
>
> The thing is I don't see how to use these tools to do what Yoahn wants 
> to do.
> I think I have the same kind of issues than Yoahn (I've done a fit, 
> how good is it as compare to another one, and what kind of 
> "confidence" or "error bar" should I associate to each parameter).
> Could you tell us how we can use interval analysis to adress this 
> (just curious, it's a bit far from my field of expertise)?
>
> Cheers,
>
> Antoine
>
>
>
>
>
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