Wow, thanks Luc.
One correction, I think. In the theoreticalValue() method, this:
return ((a.getEstimate() * x + b.getEstimate()) * x + c.getEstimate());
should be:
return ((a.getEstimate() * x * x + b.getEstimate()) * x + c.getEstimate());
> mickeydog@TaosNet.com a écrit :
>> Thanks for the reply and my apologies for omitting the [math] marker.
>>
>> Afa the model goes, I'm not sure how to answer. What I am doing is
>> smoothing a curve using the loess function, and the last step is to use
>> a
>> weighted least square regression on each point and its neighborhood.
>
> In addition to my previous message where I gave an implementation based
> on EstimationProblem and WeightedMeasurement as specified, I would like
> to say that in this very simple case, using these classes is probably
> overkill. Low degree polynomials fitting in one dimension only can be
> done very simply with a single loop updating some sums as each sample
> point is added and performing a simple direct computation to retrieve
> the polynomials coefficients at the end of the loop.
>
> EstimationProblem, EstimatedParameters and WeightedParameters are more
> suited for nonlinear problems with several different measurements types
> and parameters and complex models. The reference use case for which this
> class was created was to perform spacecraft orbit determination from
> range, rangerate, angular and more exotic measurements with a numerical
> model taking into account several perturbing forces. This requires some
> features that add to the complexity of the classes. I'm not sure using
> such heavyweight component is wise for your case. You may have
> performance issues with them.
>
> Luc
>
>>
>>
>>> Hi,
>>>
>>> First of all, I have added a [math] marker on the subject line. This
>>> list
>>> is shared among all commons projects and this type of markers help
>>> people
>>> filter the messages.
>>>
>>> I will send a usage example on the list in a few hours (late evening,
>>> european time), when I'm back home. Would you like to have anything
>> special in this example ? For example what kind of model do you want to
>> be fitted to the x,ydata ?
>>> Luc
>>>
>>> Selon mickeydog@TaosNet.com:
>>>
>>>> Can anybody show me an example of a weighted least squares regression
>>>> using classes like EstimationProblem, WeightedMeasurement from
>>>> apache.commons.math?
>>>>
>>>> I have data that looks like this: (x,y,weight), e.g.
>>>> 1,1,0.2
>>>> 2,3, 0.4
>>>> 3,2, 1.0
>>>> 4,6, 0.8
>>>> 5,4, 0.3
>>
>>
>> 
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>
>
>
> 
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