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From Gilles Sadowski <gil...@harfang.homelinux.org>
Subject Re: [math]
Date Thu, 05 Jul 2012 20:18:04 GMT
On Thu, Jul 05, 2012 at 06:16:11PM +0000, Italo Maia wrote:
> 
> Some "context" below:
> 
> Did you have a look at the classes in the package
> 
> "org.apache.commons.math3.optimization" ?
> 
> No, I did not. Let's see...
> 
> 
> Which function?
> 
> This little devil:
> 
> http://dpaste.com/hold/767050/
> 
> public static double fnc(double t, double a, double b, double c){
>         return Math.log(a) + b * Math.log(t) - c * t;
> 
> }
> 
> I have t in the matrix (first column). Second column are the observed values. I need
to fit a, b and c.
> === END
> 
> Well, the derivatives don't seem to be working.
> 
> double da = 1/a;
> double db = b/t; 
> double dc = -c;
> 

Then try
   1/a
   log(t)
   -t


Regards,
Gilles

> 
> > Date: Thu, 5 Jul 2012 19:21:46 +0200
> > From: gilles@harfang.homelinux.org
> > To: user@commons.apache.org
> > Subject: Re: [math]
> > 
> > Hi.
> > 
> > > 
> > > Thanks Giles! I was looking in the wrong place. Any suggestions on examples
for these classes (a math function example would be very nice)? I've found this link (very
helpful) but I don't know what to code in the gradient method. In ParametricUnivariateFunction.value
I just returned my function output with the params as arguments (plus x). For gradient, I'm
in a pitch.
> > 
> > And I'm lacking context (sorry, I deleted your previous email from my
> > inbox)...
> > 
> > Anyways, the "gradient(double x, double ... parameters)" method should
> > return the partial derivatives with respect to the _parameters_. So, for
> > example:
> > ---
> > public class ParamFuncExample implements ParametricUnivariateFunction {
> >   public double value(double x, double ... p) {
> >     return p[0] * x + p[1];
> >   }
> > 
> >   public double[] gradient(double x, double ... p) {
> >     return new double[] { x, 1 };
> >   }
> > }
> > ---
> > 
> > 
> > HTH,
> > Gilles
> > 
> > ---------------------------------------------------------------------
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> > 
>  		 	   		  

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