R2 values from SSErr fit.variogram attribute
On 03/15/2011 04:18 AM, S?bastien Durand wrote:
Hello Dr. Pebesma and all other 1989 readers... Believe me, I would have been much happier, if I could comprehend this tiny little detail that you refer to as :
It looks quite OK; I suspect however that instead of using mean(s.v$gamma) for SSTot, for this mean the same weighting scheme should have been used.
I still do not understand what you mean by that. I am very sorry for that and yes I now feel stupid, sincerely I am doing my best to graps very old notions. In my function, it is the weighted residual that are squared, that part is ok, but now you are telling me that I am not using to proper "mean" reference, that in fact the "same weighting scheme should be used on that ... ??? Did you meant "mean(vario$gamma)*weig" ??? I would like to receive an explanation for this?
You're comparing a weighted fit to an unweighted mean. If you want to evaluate the fit (by R2), the corresponding null-model should use the same weights, IMO. Given weights w and values sv$gamma, that would be sum(w * sv$gamma)/sum(w) rather than mean(sv$gamma). Or, alternatively, weighted.mean(sv$gamma, w)
Sincerely! The other software is GS+ S.
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Edzer Pebesma Institute for Geoinformatics (ifgi), University of M?nster Weseler Stra?e 253, 48151 M?nster, Germany. Phone: +49 251 8333081, Fax: +49 251 8339763 http://ifgi.uni-muenster.de http://www.52north.org/geostatistics e.pebesma at wwu.de