*******************************************************************************
Mon Jan 12 01:02:46 2026


FIT:    data read from DATA."/distrib_degrees_reel.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 7.9034085045e+03   0.00e+00  3.22e+00    1.000000e+00   1.000000e+00
   4 7.3525679675e+01  -1.58e-08  3.22e-04    2.342408e+00   2.705388e+00

After 4 iterations the fit converged.
final sum of squares of residuals : 73.5257
rel. change during last iteration : -1.58101e-13

degrees of freedom    (FIT_NDF)                        : 197
rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 0.610923
variance of residuals (reduced chisquare) = WSSR/ndf   : 0.373227

Final set of parameters            Asymptotic Standard Error
=======================            ==========================
lc              = 2.34241          +/- 0.1971       (8.414%)
gamma           = 2.70539          +/- 0.04437      (1.64%)

correlation matrix of the fit parameters:
                lc     gamma  
lc              1.000 
gamma           0.976  1.000 


*******************************************************************************
Mon Jan 12 01:32:31 2026


FIT:    data read from "target/dat/distrib_degrees_reel.dat" using     (($1>=kmin && $2>0) ? log($1) : 1/0):(($1>=kmin && $2>0) ? log($2) : 1/0)
        format = x:z
        x range restricted to [1.00000 : *]
        #datapoints = 190
        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 7.8600001529e+03   0.00e+00  3.28e+00    1.000000e+00   1.000000e+00
   4 3.3768536984e+01  -1.71e-06  3.28e-04    3.978305e+00   3.059786e+00

After 4 iterations the fit converged.
final sum of squares of residuals : 33.7685
rel. change during last iteration : -1.71341e-11

degrees of freedom    (FIT_NDF)                        : 188
rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 0.423816
variance of residuals (reduced chisquare) = WSSR/ndf   : 0.17962

Final set of parameters            Asymptotic Standard Error
=======================            ==========================
lc              = 3.9783           +/- 0.187        (4.7%)
gamma           = 3.05979          +/- 0.04125      (1.348%)

correlation matrix of the fit parameters:
                lc     gamma  
lc              1.000 
gamma           0.986  1.000 


*******************************************************************************
Mon Jan 12 01:42:59 2026


FIT:    data read from file using (($1>=kmin) ? $1 : 1/0):2
        format = x:z
        x range restricted to [1.00000 : 1000.00]
        #datapoints = 190
        residuals are weighted equally (unit weight)

function used for fitting: power(x)
	power(x) = c * x**(-gammaP)
fitted parameters initialized with current variable values

iter      chisq       delta/lim  lambda   c             gammaP       
   0 1.1717010350e-03   0.00e+00  1.80e-03    1.000000e+00   2.500000e+00
  18 3.0102500012e-06  -5.63e-03  1.80e-04    3.640255e+00   2.229983e+00

After 18 iterations the fit converged.
final sum of squares of residuals : 3.01025e-06
rel. change during last iteration : -5.63118e-08

degrees of freedom    (FIT_NDF)                        : 188
rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 0.000126538
variance of residuals (reduced chisquare) = WSSR/ndf   : 1.6012e-08

Final set of parameters            Asymptotic Standard Error
=======================            ==========================
c               = 3.64025          +/- 0.1039       (2.855%)
gammaP          = 2.22998          +/- 0.01118      (0.5015%)

correlation matrix of the fit parameters:
                c      gammaP 
c               1.000 
gammaP          0.994  1.000