******************************************************************************* Fri Sep 8 09:39:54 2023 FIT: data read from 'MARK_INFLECTOR_DS_phase_space.dat' u 9:36 format = x:z #datapoints = 97788 residuals are weighted equally (unit weight) function used for fitting: f(x) f(x) = a+b*x fitted parameters initialized with current variable values iter chisq delta/lim lambda a b 0 1.5719713844e+05 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00 2 1.0168606776e+04 -2.70e-01 7.07e-03 2.228533e+00 -6.395200e-01 After 2 iterations the fit converged. final sum of squares of residuals : 10168.6 rel. change during last iteration : -2.69638e-06 degrees of freedom (FIT_NDF) : 97786 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.322472 variance of residuals (reduced chisquare) = WSSR/ndf : 0.103988 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 2.22853 +/- 0.001037 (0.04652%) b = -0.63952 +/- 0.06642 (10.39%) correlation matrix of the fit parameters: a b a 1.000 b -0.102 1.000 ******************************************************************************* Fri Sep 8 09:42:03 2023 FIT: data read from 'DistStartInjLine_phase_space.dat' u 9:36 format = x:z #datapoints = 150000 residuals are weighted equally (unit weight) function used for fitting: f(x) f(x) = a+b*x fitted parameters initialized with current variable values iter chisq delta/lim lambda a b 0 1.6246506671e+04 0.00e+00 1.58e+00 2.228533e+00 -6.395200e-01 2 1.6159878983e+04 -1.29e-01 1.58e-02 2.204810e+00 -8.084682e-01 After 2 iterations the fit converged. final sum of squares of residuals : 16159.9 rel. change during last iteration : -1.28919e-06 degrees of freedom (FIT_NDF) : 149998 rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.328229 variance of residuals (reduced chisquare) = WSSR/ndf : 0.107734 Final set of parameters Asymptotic Standard Error ======================= ========================== a = 2.20481 +/- 0.000849 (0.03851%) b = -0.808468 +/- 0.05367 (6.638%) correlation matrix of the fit parameters: a b a 1.000 b -0.060 1.000