Hi all, I had used the gnuplot as well as the GSL facilities for fitting my experimental data by power law y~ b*x^a. When I approximate data by linear algorithm (in logarithmic variables) both gnuplot and GSL give the same results. But if data had been approximated directly by power law and nonlinear fitting algorithm, the GSL fit give the same results, as gnuplot, but with sufficiently greater error estimates. The heart is that in GSL, against to gnuplot, for poor fit (when the chi-squared per degree of freedom (dof) is greater then 1) errors obtained from the covariance matrix are scaled by factor sqrt(chi^2/dof)
So, what approach is more correct? Cheers, Stanislav. _______________________________________________ Help-gsl mailing list [email protected] http://lists.gnu.org/mailman/listinfo/help-gsl
