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());
> [EMAIL PROTECTED] 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 non-linear 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, range-rate, 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 [EMAIL PROTECTED]: >>> >>>> 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 >> >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: [EMAIL PROTECTED] >> For additional commands, e-mail: [EMAIL PROTECTED] >> >> > > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [EMAIL PROTECTED] > For additional commands, e-mail: [EMAIL PROTECTED] > --------------------------------------------------------------------- To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
