> From: uwe.wolf...@uni-ulm.de
> To: andy_l...@merck.com
> Date: Sat, 5 Mar 2011 17:14:12 +0100
> CC: r-help@r-project.org; gunter.ber...@gene.com
> Subject: Re: [R] Coefficient of Determination for nonlinear function
>
>
un...@r-project.org] On Behalf Of Bert Gunter
> > Sent: Friday, March 04, 2011 11:21 AM
> > To: uwe.wolf...@uni-ulm.de; r-help@r-project.org
> > Subject: Re: [R] Coefficient of Determination for nonlinear function
> >
> > The coefficient of determination, R^2, is a
Uwe Wolfram wrote:
>
>
> I did fit an equation of the form 1 = f(x1,x2,x3) using a minimization
> scheme. Now I want to compute the coefficient of determination. Normally
> I would compute it as
>
> r_square = 1- sserr/sstot with sserr = sum_i (y_i - f_i) and sstot =
> sum_i (y_i - mean(y))
>
tical measure.
>
> Andy
>
>> -Original Message-
>> From: r-help-boun...@r-project.org
>> [mailto:r-help-boun...@r-project.org] On Behalf Of Bert Gunter
>> Sent: Friday, March 04, 2011 11:21 AM
>> To: uwe.wolf...@uni-ulm.de; r-help@r-project.org
>> Sub
rom: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of Bert Gunter
> Sent: Friday, March 04, 2011 11:21 AM
> To: uwe.wolf...@uni-ulm.de; r-help@r-project.org
> Subject: Re: [R] Coefficient of Determination for nonlinear function
>
> The coefficient
The coefficient of determination, R^2, is a measure of how well your
model fits versus a "NULL" model, which is that the data are constant.
In nonlinear models, as opposed to linear models, such a null model
rarely makes sense. Therefore the coefficient of determination is
generally not meaningful
Dear Subscribers,
I did fit an equation of the form 1 = f(x1,x2,x3) using a minimization
scheme. Now I want to compute the coefficient of determination. Normally
I would compute it as
r_square = 1- sserr/sstot with sserr = sum_i (y_i - f_i) and sstot =
sum_i (y_i - mean(y))
sserr is clear to me
Dear Subscribers,
I did fit an equation of the form 1 = f(x1,x2,x3) using a minimization
scheme. Now I want to compute the coefficient of determination. Normally
I would compute it as
r_square = 1- sserr/sstot with sserr = sum_i (y_i - f_i) and sstot =
sum_i (y_i - mean(y))
sserr is clear to me
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