As Bert Gunter points out, the statistic R-squared should not be given any
grand meaning.
However, (also in the archives) I use it in my nonlinear least squares codes as
a "sanity
check" -- and not more than that. Since it is computed as
{1 - (residual SS)/(SS from mean)},
do you really want to use a model if it does little better than a model that is
simply the
data mean?
I find it useful to run easy-to-compute sanity checks as a way to avoid putting
foot in
mouth, especially now that computers create output so prodigiously.
JN
On 04/26/2012 06:00 AM, r-help-requ...@r-project.org wrote:
> Message: 54
> Date: Wed, 25 Apr 2012 17:12:52 +0200
> From: Pierre Grison <pgri...@hotmail.fr>
> To: <r-h...@stat.math.ethz.ch>
> Subject: [R] r-square for non-linear regression
> Message-ID: <blu0-smtp2288e7041d27f9e634c3331c4...@phx.gbl>
> Content-Type: text/plain
>
> Hi,
>
> I saw you discussed about the meaning of the R squared in a nls regression.
> Do you have a source or a quotation please?
>
> kind regards,
>
> Pierre Grison
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