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Date: Sat, 7 Jul 2012 00:29:51 +0200
From: Gilles Sadowski <gilles@harfang.homelinux.org>
To: user@commons.apache.org
Subject: Re: [math]
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On Fri, Jul 06, 2012 at 09:39:30PM +0000, Italo Maia wrote:
> 
> Hummm, so my assumption that my previous values for a, b and c were the best are wrong. I calculated the resid and it is really smaller. Real thanks for that!

I wouldn't take the difference too seriously, given that the data are not
really close to the curve. The errors seem quite large.

> Any tips on calculating the r-squared?

No.

Gilles

> 
> Date: Fri, 6 Jul 2012 22:05:26 +0200
> From: gilles@harfang.homelinux.org
> To: user@commons.apache.org
> Subject: Re: [math]
> 
> Hi.
>  
> If you are using the function
>  
>   a * Math.pow(t, b) * Math.exp(-c * t)
>  
> the gradient is:
>  
>   { Math.pow(t, b) * Math.exp(-c * t),
>     a * Math.log(t) * Math.pow(t, b) * Math.exp(-c * t),
>     -a * t  Math.pow(t, b) * Math.exp(-c * t) }
>  
> > // No idea what goes here. Nothing seems to work.
>  
> Well, the gradient (partial derivatives w.r.t the parameters) is the thing
> that will work; the attached figure shows the data and the function that
> fits it with
>  a = 1.097378664278161
>  b = 0.4273818336149512
>  c = 0.01457006142420487
>  
> > 
> > a, b and c for this example should be: A: 1.0782   B: 0.4583   C: 0.0166
>  
> The fit is slightly better with the values found by "CurveFitter"
> (the "LevenbergMarquardt" algorithm actually).
>  
> Regards,
> Gilles
>  
> 
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