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Liza Ait Braham
a validé
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*******************************************************************************
Fri Nov 28 08:32:22 2025
FIT: data read from 'degreeDist_dblp.dat' using (log($1)):(log($2))
format = x:z
#datapoints = 199
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = lc - gamma * x
fitted parameters initialized with current variable values
iter chisq delta/lim lambda lc gamma
0 7.9039213112e+03 0.00e+00 3.22e+00 1.000000e+00 1.000000e+00
4 7.3562572818e+01 -1.58e-08 3.22e-04 2.342979e+00 2.705555e+00
After 4 iterations the fit converged.
final sum of squares of residuals : 73.5626
rel. change during last iteration : -1.58215e-13
degrees of freedom (FIT_NDF) : 197
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.611076
variance of residuals (reduced chisquare) = WSSR/ndf : 0.373414
Final set of parameters Asymptotic Standard Error
======================= ==========================
lc = 2.34298 +/- 0.1971 (8.414%)
gamma = 2.70556 +/- 0.04438 (1.64%)
correlation matrix of the fit parameters:
lc gamma
lc 1.000
gamma 0.976 1.000
*******************************************************************************
Fri Nov 28 08:35:38 2025
FIT: data read from 'degreeDist_dblp.dat' using (log($1)):(log($2))
format = x:z
#datapoints = 199
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = lc - gamma * x
fitted parameters initialized with current variable values
iter chisq delta/lim lambda lc gamma
0 7.9039213112e+03 0.00e+00 3.22e+00 1.000000e+00 1.000000e+00
4 7.3562572818e+01 -1.58e-08 3.22e-04 2.342979e+00 2.705555e+00
After 4 iterations the fit converged.
final sum of squares of residuals : 73.5626
rel. change during last iteration : -1.58215e-13
degrees of freedom (FIT_NDF) : 197
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.611076
variance of residuals (reduced chisquare) = WSSR/ndf : 0.373414
Final set of parameters Asymptotic Standard Error
======================= ==========================
lc = 2.34298 +/- 0.1971 (8.414%)
gamma = 2.70556 +/- 0.04438 (1.64%)
correlation matrix of the fit parameters:
lc gamma
lc 1.000
gamma 0.976 1.000
*******************************************************************************
Fri Nov 28 08:38:03 2025
FIT: data read from 'degreeDist_dblp.dat' using (log($1)):(log($2))
format = x:z
#datapoints = 199
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = lc - gamma * x
fitted parameters initialized with current variable values
iter chisq delta/lim lambda lc gamma
0 7.3562572818e+01 0.00e+00 8.66e+00 2.342979e+00 2.705555e+00
1 7.3562572818e+01 -1.93e-11 8.66e-01 2.342979e+00 2.705555e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 73.5626
rel. change during last iteration : -1.93181e-16
degrees of freedom (FIT_NDF) : 197
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.611076
variance of residuals (reduced chisquare) = WSSR/ndf : 0.373414
Final set of parameters Asymptotic Standard Error
======================= ==========================
lc = 2.34298 +/- 0.1971 (8.414%)
gamma = 2.70556 +/- 0.04438 (1.64%)
correlation matrix of the fit parameters:
lc gamma
lc 1.000
gamma 0.976 1.000
*******************************************************************************
Fri Nov 28 08:38:56 2025
FIT: data read from 'degreeDist_dblp.dat' using (log($1)):(log($2))
format = x:z
#datapoints = 199
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = lc - gamma * x
fitted parameters initialized with current variable values
iter chisq delta/lim lambda lc gamma
0 7.3562572818e+01 0.00e+00 8.66e+00 2.342979e+00 2.705555e+00
1 7.3562572818e+01 0.00e+00 8.66e-01 2.342979e+00 2.705555e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 73.5626
rel. change during last iteration : 0
degrees of freedom (FIT_NDF) : 197
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.611076
variance of residuals (reduced chisquare) = WSSR/ndf : 0.373414
Final set of parameters Asymptotic Standard Error
======================= ==========================
lc = 2.34298 +/- 0.1971 (8.414%)
gamma = 2.70556 +/- 0.04438 (1.64%)
correlation matrix of the fit parameters:
lc gamma
lc 1.000
gamma 0.976 1.000
*******************************************************************************
Fri Nov 28 08:39:35 2025
FIT: data read from 'degreeDist_dblp.dat' using (log($1)):(log($2))
format = x:z
#datapoints = 199
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = lc - gamma * x
fitted parameters initialized with current variable values
iter chisq delta/lim lambda lc gamma
0 7.3562572818e+01 0.00e+00 8.66e+00 2.342979e+00 2.705555e+00
1 7.3562572818e+01 -1.93e-11 8.66e+00 2.342979e+00 2.705555e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 73.5626
rel. change during last iteration : -1.93181e-16
degrees of freedom (FIT_NDF) : 197
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.611076
variance of residuals (reduced chisquare) = WSSR/ndf : 0.373414
Final set of parameters Asymptotic Standard Error
======================= ==========================
lc = 2.34298 +/- 0.1971 (8.414%)
gamma = 2.70556 +/- 0.04438 (1.64%)
correlation matrix of the fit parameters:
lc gamma
lc 1.000
gamma 0.976 1.000
*******************************************************************************
Fri Nov 28 08:40:33 2025
FIT: data read from 'degreeDist_dblp.dat' using (log($1)):(log($2))
format = x:z
#datapoints = 199
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = lc - gamma * x
fitted parameters initialized with current variable values
iter chisq delta/lim lambda lc gamma
0 7.9039213112e+03 0.00e+00 3.22e+00 1.000000e+00 1.000000e+00
4 7.3562572818e+01 -1.58e-08 3.22e-04 2.342979e+00 2.705555e+00
After 4 iterations the fit converged.
final sum of squares of residuals : 73.5626
rel. change during last iteration : -1.58215e-13
degrees of freedom (FIT_NDF) : 197
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.611076
variance of residuals (reduced chisquare) = WSSR/ndf : 0.373414
Final set of parameters Asymptotic Standard Error
======================= ==========================
lc = 2.34298 +/- 0.1971 (8.414%)
gamma = 2.70556 +/- 0.04438 (1.64%)
correlation matrix of the fit parameters:
lc gamma
lc 1.000
gamma 0.976 1.000