

*******************************************************************************
Tue Oct 24 02:36:17 2017


FIT:    data read from "gradient.csv" every ::1 using 2:5
        format = x:z
        #datapoints = 305
        residuals are weighted equally (unit weight)

function used for fitting: f(x)
fitted parameters initialized with current variable values



 Iteration 0
 WSSR        : 1.35967e+07       delta(WSSR)/WSSR   : 0
 delta(WSSR) : 0                 limit for stopping : 1e-05
 lambda	  : 0.707243

initial set of free parameter values

a               = 1
b               = 1

After 4 iterations the fit converged.
final sum of squares of residuals : 773379
rel. change during last iteration : -8.7995e-07

degrees of freedom    (FIT_NDF)                        : 303
rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 50.5213
variance of residuals (reduced chisquare) = WSSR/ndf   : 2552.4

Final set of parameters            Asymptotic Standard Error
=======================            ==========================

a               = -3455.11         +/- 597.4        (17.29%)
b               = 271.216          +/- 11.74        (4.33%)


correlation matrix of the fit parameters:

               a      b      
a               1.000 
b              -0.969  1.000 


*******************************************************************************
Tue Oct 24 02:36:17 2017


FIT:    data read from "gradient.csv" every ::1 using 4:5
        format = x:z
        #datapoints = 305
        residuals are weighted equally (unit weight)

function used for fitting: g(x)
fitted parameters initialized with current variable values



 Iteration 0
 WSSR        : 1.3481e+07        delta(WSSR)/WSSR   : 0
 delta(WSSR) : 0                 limit for stopping : 1e-05
 lambda	  : 0.974091

initial set of free parameter values

aa              = 1
bb              = 1

After 4 iterations the fit converged.
final sum of squares of residuals : 799152
rel. change during last iteration : -9.18053e-10

degrees of freedom    (FIT_NDF)                        : 303
rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 51.3562
variance of residuals (reduced chisquare) = WSSR/ndf   : 2637.46

Final set of parameters            Asymptotic Standard Error
=======================            ==========================

aa              = 647.632          +/- 136.2        (21.03%)
bb              = -408.074         +/- 129.1        (31.63%)


correlation matrix of the fit parameters:

               aa     bb     
aa              1.000 
bb             -1.000  1.000 


*******************************************************************************
Tue Oct 24 02:36:17 2017


FIT:    data read from "gradient.csv" every ::1 using 4:6
        format = x:z
        #datapoints = 305
        residuals are weighted equally (unit weight)

function used for fitting: h(x)
fitted parameters initialized with current variable values



 Iteration 0
 WSSR        : 1.4212e+07        delta(WSSR)/WSSR   : 0
 delta(WSSR) : 0                 limit for stopping : 1e-05
 lambda	  : 0.974091

initial set of free parameter values

aaa             = 1
bbb             = 1

After 4 iterations the fit converged.
final sum of squares of residuals : 146702
rel. change during last iteration : -2.79543e-10

degrees of freedom    (FIT_NDF)                        : 303
rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 22.0038
variance of residuals (reduced chisquare) = WSSR/ndf   : 484.166

Final set of parameters            Asymptotic Standard Error
=======================            ==========================

aaa             = -20.6354         +/- 58.36        (282.8%)
bbb             = 236.239          +/- 55.3         (23.41%)


correlation matrix of the fit parameters:

               aaa    bbb    
aaa             1.000 
bbb            -1.000  1.000 


*******************************************************************************
Tue Oct 24 02:36:17 2017


FIT:    data read from "gradient.csv" every ::1 using 3:6
        format = x:z
        #datapoints = 305
        residuals are weighted equally (unit weight)

function used for fitting: i(x)
fitted parameters initialized with current variable values



 Iteration 0
 WSSR        : 1.43362e+07       delta(WSSR)/WSSR   : 0
 delta(WSSR) : 0                 limit for stopping : 1e-05
 lambda	  : 0.707107

initial set of free parameter values

aaaa            = 1
bbbb            = 1

After 3 iterations the fit converged.
final sum of squares of residuals : 146763
rel. change during last iteration : -6.86135e-14

degrees of freedom    (FIT_NDF)                        : 303
rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 22.0083
variance of residuals (reduced chisquare) = WSSR/ndf   : 484.366

Final set of parameters            Asymptotic Standard Error
=======================            ==========================

aaaa            = 1.23966          +/- 4.167e+17    (3.362e+19%)
bbbb            = 216.691          +/- 4.63e+14     (2.137e+14%)


correlation matrix of the fit parameters:

               aaaa   bbbb   
aaaa            1.000 
bbbb           -1.000  1.000 
