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From Ted Dunning <ted.dunn...@gmail.com>
Subject Re: curve fitting ax^b
Date Wed, 26 Aug 2009 21:23:54 GMT
```What you are suggesting will (roughly) work, but you might consider just
fitting log x versus log y.

Your error terms will not be squared error, but instead will be squared
relative error.

On Wed, Aug 26, 2009 at 2:19 PM, Fabio Cerqueira <frcerqueira@gmail.com>wrote:

> Hello,
>
> I need to perform curve fitting where the function is of the form: ax^b.
> I saw that polynomial fitting is already implemented in
> commons.math, but a function like the one I need is not.
>
> Then I found the CurveFitter class and proceeded like below,
> but I haven't succeeded. Any suggestion?
>
> Thanks, Fabio
>
> class PowerFunction implements ParametricRealFunction {
>
>  // overriding
>  public double[] gradient(double x, double[] parameters) {
>    double vet[] = new double[10];
>    double coef, exp, newExp, coefTimesExp, power;
>
>    if ( x==0 ) {
>      vet[0] = 0;
>    }
>    else {
>      coef = parameters[0];
>      exp = parameters[1];
>      coefTimesExp = coef * exp;
>      newExp = exp-1;
>      power = Math.pow( x, newExp );
>      vet[0] = coefTimesExp * power;
>    }
>    return vet;
>
>  // overriding
>  public double value(double x, double[] parameters) {
>    double coef, exp, power;
>    coef = parameters[0];
>    exp = parameters[1];
>    power = Math.pow( x, exp );
>
>    return ( coef * power );
>  } // value
>
> } // class PowerFunction
>

--
Ted Dunning, CTO
DeepDyve

```
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