masterarbeit/dokumentation/evolution1d/20171005-all.gnuplot.fit.log

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2017-10-05 12:27:39 +00:00
*******************************************************************************
Thu Oct 5 14:24:23 2017
FIT: data read from "20171005-all.csv" every ::1 using 2:5
format = x:z
#datapoints = 500
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 2.2819584538e+07 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
4 9.2387072945e+05 -3.77e-04 7.07e-05 5.253352e+02 1.999370e+02
After 4 iterations the fit converged.
final sum of squares of residuals : 923871
rel. change during last iteration : -3.77204e-09
degrees of freedom (FIT_NDF) : 498
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 43.0716
variance of residuals (reduced chisquare) = WSSR/ndf : 1855.16
Final set of parameters Asymptotic Standard Error
======================= ==========================
a = 525.335 +/- 371.3 (70.69%)
b = 199.937 +/- 7.551 (3.777%)
correlation matrix of the fit parameters:
a b
a 1.000
b -0.967 1.000
*******************************************************************************
Thu Oct 5 14:24:23 2017
FIT: data read from "20171005-all.csv" every ::1 using 4:5
format = x:z
#datapoints = 500
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 2.2629211027e+07 0.00e+00 9.66e-01 1.000000e+00 1.000000e+00
4 8.9631538551e+05 -2.78e-05 9.66e-05 4.610660e+02 -2.189272e+02
After 4 iterations the fit converged.
final sum of squares of residuals : 896315
rel. change during last iteration : -2.77934e-10
degrees of freedom (FIT_NDF) : 498
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 42.4244
variance of residuals (reduced chisquare) = WSSR/ndf : 1799.83
Final set of parameters Asymptotic Standard Error
======================= ==========================
aa = 461.066 +/- 110.6 (23.99%)
bb = -218.927 +/- 103 (47.04%)
correlation matrix of the fit parameters:
aa bb
aa 1.000
bb -1.000 1.000
*******************************************************************************
Thu Oct 5 14:24:23 2017
FIT: data read from "20171005-all.csv" every ::1 using 4:6
format = x:z
#datapoints = 500
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 2.4597834778e+07 0.00e+00 9.66e-01 1.000000e+00 1.000000e+00
5 4.4603658393e+01 -1.73e-08 9.66e-06 -3.139922e+03 3.139954e+03
After 5 iterations the fit converged.
final sum of squares of residuals : 44.6037
rel. change during last iteration : -1.72842e-13
degrees of freedom (FIT_NDF) : 498
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.299275
variance of residuals (reduced chisquare) = WSSR/ndf : 0.0895656
Final set of parameters Asymptotic Standard Error
======================= ==========================
aaa = -3139.92 +/- 0.7803 (0.02485%)
bbb = 3139.95 +/- 0.7265 (0.02314%)
correlation matrix of the fit parameters:
aaa bbb
aaa 1.000
bbb -1.000 1.000
*******************************************************************************
Thu Oct 5 14:24:23 2017
FIT: data read from "20171005-all.csv" every ::1 using 3:6
format = x:z
#datapoints = 500
residuals are weighted equally (unit weight)
function used for fitting: i(x)
i(x)=aaaa*x+bbbb
fitted parameters initialized with current variable values
iter chisq delta/lim lambda aaaa bbbb
0 2.4797348325e+07 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
5 6.2575820484e+05 -6.78e-01 7.07e-06 -1.004063e+05 3.554273e+02
After 5 iterations the fit converged.
final sum of squares of residuals : 625758
rel. change during last iteration : -6.77885e-06
degrees of freedom (FIT_NDF) : 498
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 35.4477
variance of residuals (reduced chisquare) = WSSR/ndf : 1256.54
Final set of parameters Asymptotic Standard Error
======================= ==========================
aaaa = -100406 +/- 3920 (3.904%)
bbbb = 355.427 +/- 5.629 (1.584%)
correlation matrix of the fit parameters:
aaaa bbbb
aaaa 1.000
bbbb -0.960 1.000