******************************************************************************* Thu Oct 5 14:02:37 2017 FIT: data read from "20171005-evolution1D_7x4_100Times.csv" every ::1 using 2:5 format = x:z #datapoints = 100 residuals are weighted equally (unit weight) function used for fitting: f(x) f(x)=a*x+b fitted parameters initialized with current variable values iter chisq delta/lim lambda a b 0 4.2059624024e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00 5 1.6157855782e+05 -1.28e-04 7.07e-06 -3.703035e+03 2.609538e+02 After 5 iterations the fit converged. final sum of squares of residuals : 161579 rel. change during last iteration : -1.2809e-09 degrees of freedom (FIT_NDF) : 98 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.6049 variance of residuals (reduced chisquare) = WSSR/ndf : 1648.76 Final set of parameters Asymptotic Standard Error ======================= ========================== a = -3703.04 +/- 2343 (63.28%) b = 260.954 +/- 37.51 (14.38%) correlation matrix of the fit parameters: a b a 1.000 b -0.994 1.000 ******************************************************************************* Thu Oct 5 14:02:37 2017 FIT: data read from "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:5 format = x:z #datapoints = 100 residuals are weighted equally (unit weight) function used for fitting: g(x) g(x)=aa*x+bb fitted parameters initialized with current variable values iter chisq delta/lim lambda aa bb 0 4.1694597860e+06 0.00e+00 9.64e-01 1.000000e+00 1.000000e+00 5 1.6088124752e+05 -2.98e-05 9.64e-06 1.779074e+03 -1.445031e+03 After 5 iterations the fit converged. final sum of squares of residuals : 160881 rel. change during last iteration : -2.98408e-10 degrees of freedom (FIT_NDF) : 98 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.5172 variance of residuals (reduced chisquare) = WSSR/ndf : 1641.65 Final set of parameters Asymptotic Standard Error ======================= ========================== aa = 1779.07 +/- 1039 (58.39%) bb = -1445.03 +/- 961.8 (66.56%) correlation matrix of the fit parameters: aa bb aa 1.000 bb -1.000 1.000 ******************************************************************************* Thu Oct 5 14:02:37 2017 FIT: data read from "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:6 format = x:z #datapoints = 100 residuals are weighted equally (unit weight) function used for fitting: h(x) h(x)=aaa*x+bbb fitted parameters initialized with current variable values iter chisq delta/lim lambda aaa bbb 0 5.3588910602e+06 0.00e+00 9.64e-01 1.000000e+00 1.000000e+00 6 5.4694656646e+00 -5.96e-09 9.64e-07 -3.141932e+03 3.141867e+03 After 6 iterations the fit converged. final sum of squares of residuals : 5.46947 rel. change during last iteration : -5.95966e-14 degrees of freedom (FIT_NDF) : 98 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.236243 variance of residuals (reduced chisquare) = WSSR/ndf : 0.0558109 Final set of parameters Asymptotic Standard Error ======================= ========================== aaa = -3141.93 +/- 6.057 (0.1928%) bbb = 3141.87 +/- 5.608 (0.1785%) correlation matrix of the fit parameters: aaa bbb aaa 1.000 bbb -1.000 1.000