Hi, using "reglin" or "regress" a linear regression of measurement data can be done. But how is it possible to get Rsquared of the regression as a parameter for the "goodness of fit"? Is there another function for doing this? Thanks XMMS2010

Paul Carrico 
Hi I do as follow … but maybe there’s another way ! F_mean = mean(experience(:,2)); SSE = 0; SST = 0; SSE = norm ((F_fit(:,2)  experience(:,2))^2) ; ……. you can use sum instead of norm SST = norm((F_mean  experience(:,2))^2) ; R_square = 1  (SSE / SST); Where “experience” are the experimental data / F_fit are the results from you’re Paul De : [hidden email] [mailto:[hidden email]] Hi,

Samuel GOUGEON3 
In reply to this post by XMMS2010
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De : [hidden email] Date : 06/12/2010 21:19: The RMS deviations between data and the fit are given on the diagonal of the third output argument of reglin(). For instance. Regards Samuel 
Eric Dubois 
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Hi.
R square and many other statistics are available in Grocer, the econometric toolbox available at http://dubois.ensae.net/grocer.html or through the module manager Atoms. Éric. 2010/12/6 <[hidden email]>

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