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fit.log
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*******************************************************************************
Tue Oct 3 18:55:27 2023
FIT: data read from './benchmark/easy/stats-3505.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 4.9123594825e+01 0.00e+00 4.12e+00 1.000000e+00 1.000000e+00
5 5.8592157562e+00 -6.17e-05 4.12e-05 -5.921729e-01 8.097732e+00
After 5 iterations the fit converged.
final sum of squares of residuals : 5.85922
rel. change during last iteration : -6.17041e-10
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.855805
variance of residuals (reduced chisquare) = WSSR/ndf : 0.732402
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = -0.592173 +/- 1.033 (174.4%)
b = 8.09773 +/- 5.932 (73.26%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.999 1.000
*******************************************************************************
Tue Oct 3 19:00:24 2023
FIT: data read from './benchmark/easy/stats-3767.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 4.9556777847e+04 0.00e+00 8.84e-01 1.000000e+00 1.000000e+00
4 6.1457432157e+01 -3.59e-01 8.84e-05 -1.294892e+01 8.181076e+01
After 4 iterations the fit converged.
final sum of squares of residuals : 61.4574
rel. change during last iteration : -3.59491e-06
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 2.77167
variance of residuals (reduced chisquare) = WSSR/ndf : 7.68218
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = -12.9489 +/- 19.34 (149.4%)
b = 81.8108 +/- 14.53 (17.76%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.998 1.000
*******************************************************************************
Tue Oct 3 19:03:33 2023
FIT: data read from './benchmark/easy/stats-3902.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 1.7163190083e+02 0.00e+00 7.35e-01 1.000000e+00 1.000000e+00
4 1.0099561396e+01 -1.17e-01 7.35e-05 -5.962880e-01 5.467515e+00
After 4 iterations the fit converged.
final sum of squares of residuals : 10.0996
rel. change during last iteration : -1.17481e-06
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.12359
variance of residuals (reduced chisquare) = WSSR/ndf : 1.26245
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = -0.596288 +/- 31.99 (5365%)
b = 5.46752 +/- 8.995 (164.5%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.999 1.000
*******************************************************************************
Tue Oct 3 21:33:40 2023
FIT: data read from './benchmark/easy/stats-34.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 2.1918495859e+02 0.00e+00 8.33e-01 1.000000e+00 1.000000e+00
4 9.2010147973e+00 -1.19e-01 8.33e-05 7.819829e+00 1.344575e+00
After 4 iterations the fit converged.
final sum of squares of residuals : 9.20101
rel. change during last iteration : -1.18609e-06
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.07244
variance of residuals (reduced chisquare) = WSSR/ndf : 1.15013
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 7.81983 +/- 13.28 (169.8%)
b = 1.34457 +/- 8.251 (613.6%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.999 1.000
*******************************************************************************
Tue Oct 3 21:41:34 2023
FIT: data read from './benchmark/easy/stats-169.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 6.4825289013e+01 0.00e+00 4.20e+00 1.000000e+00 1.000000e+00
5 9.3663242274e+00 -1.78e-04 4.20e-05 -1.408040e+00 1.732616e+01
After 5 iterations the fit converged.
final sum of squares of residuals : 9.36632
rel. change during last iteration : -1.77562e-09
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.08203
variance of residuals (reduced chisquare) = WSSR/ndf : 1.17079
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = -1.40804 +/- 1.23 (87.37%)
b = 17.3262 +/- 7.196 (41.53%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.999 1.000
*******************************************************************************
Tue Oct 3 21:43:11 2023
FIT: data read from './benchmark/easy/stats-304.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 1.0724884570e+02 0.00e+00 4.49e+00 1.000000e+00 1.000000e+00
5 6.5805432155e+00 -1.11e-06 4.49e-05 -5.611010e-01 7.704599e+00
After 5 iterations the fit converged.
final sum of squares of residuals : 6.58054
rel. change during last iteration : -1.10526e-11
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.906955
variance of residuals (reduced chisquare) = WSSR/ndf : 0.822568
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = -0.561101 +/- 0.504 (89.83%)
b = 7.7046 +/- 3.161 (41.03%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.996 1.000
*******************************************************************************
Tue Oct 3 21:56:56 2023
FIT: data read from './benchmark/easy/stats-527.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 5.1373692274e+02 0.00e+00 7.16e+00 1.000000e+00 1.000000e+00
5 6.9373581961e+00 -3.06e-03 7.16e-05 -6.267347e-01 1.031029e+01
After 5 iterations the fit converged.
final sum of squares of residuals : 6.93736
rel. change during last iteration : -3.06057e-08
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.93122
variance of residuals (reduced chisquare) = WSSR/ndf : 0.86717
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = -0.626735 +/- 0.5662 (90.34%)
b = 10.3103 +/- 5.708 (55.36%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.999 1.000
*******************************************************************************
Tue Oct 3 22:10:24 2023
FIT: data read from './benchmark/easy/stats-976.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 7.7035761385e+00 0.00e+00 2.09e+00 1.000000e+00 1.000000e+00
4 6.6928170421e+00 -6.20e-02 2.09e-04 1.342798e+00 3.613722e-01
After 4 iterations the fit converged.
final sum of squares of residuals : 6.69282
rel. change during last iteration : -6.1982e-07
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.91466
variance of residuals (reduced chisquare) = WSSR/ndf : 0.836602
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 1.3428 +/- 2.698 (200.9%)
b = 0.361372 +/- 7.518 (2080%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.999 1.000
*******************************************************************************
Thu Oct 5 17:06:47 2023
FIT: data read from './benchmark/easy/stats-3499.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 1.8061344392e+01 0.00e+00 2.19e+00 1.000000e+00 1.000000e+00
5 5.3648936851e+00 -5.10e-06 2.19e-05 -6.466092e+00 2.348284e+01
After 5 iterations the fit converged.
final sum of squares of residuals : 5.36489
rel. change during last iteration : -5.09702e-11
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.818909
variance of residuals (reduced chisquare) = WSSR/ndf : 0.670612
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = -6.46609 +/- 1.982 (30.66%)
b = 23.4828 +/- 5.825 (24.81%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.999 1.000
*******************************************************************************
Thu Oct 5 17:08:01 2023
FIT: data read from './benchmark/medium/stats-3636.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 7.4134923885e+00 0.00e+00 2.17e+00 1.000000e+00 1.000000e+00
5 3.2839538914e+00 -8.35e-05 2.17e-05 -5.593477e+00 2.041054e+01
After 5 iterations the fit converged.
final sum of squares of residuals : 3.28395
rel. change during last iteration : -8.35457e-10
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.640698
variance of residuals (reduced chisquare) = WSSR/ndf : 0.410494
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = -5.59348 +/- 2.355 (42.1%)
b = 20.4105 +/- 6.828 (33.45%)
correlation matrix of the fit parameters:
m b
m 1.000
b -1.000 1.000
*******************************************************************************
Sat Oct 7 14:10:21 2023
FIT: data read from './benchmark/easy/stats-488.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 3.7661607995e+02 0.00e+00 6.61e+00 1.000000e+00 1.000000e+00
5 2.8587135976e+00 -1.99e-01 6.61e-05 -1.061582e+00 1.406280e+01
After 5 iterations the fit converged.
final sum of squares of residuals : 2.85871
rel. change during last iteration : -1.99327e-06
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.597779
variance of residuals (reduced chisquare) = WSSR/ndf : 0.357339
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = -1.06158 +/- 0.7371 (69.43%)
b = 14.0628 +/- 6.85 (48.71%)
correlation matrix of the fit parameters:
m b
m 1.000
b -1.000 1.000
*******************************************************************************
Sat Oct 7 14:21:17 2023
FIT: data read from './benchmark/easy/stats-623.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 2.2913757283e+04 0.00e+00 3.56e+01 1.000000e+00 1.000000e+00
5 2.6810378871e+00 -1.43e-03 3.56e-04 3.072585e-02 1.911518e+00
After 5 iterations the fit converged.
final sum of squares of residuals : 2.68104
rel. change during last iteration : -1.42775e-08
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.578904
variance of residuals (reduced chisquare) = WSSR/ndf : 0.33513
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 0.0307259 +/- 0.01357 (44.15%)
b = 1.91152 +/- 0.6822 (35.69%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.963 1.000
*******************************************************************************
Sat Oct 7 14:41:58 2023
FIT: data read from './benchmark/easy/stats-7720.txt' using 1:2
format = x:z
#datapoints = 2
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 2.8308984884e+02 0.00e+00 1.06e+01 1.000000e+00 1.000000e+00
20 4.0636197380e-27 0.00e+00 1.06e+01 1.359482e-13 4.000000e+00
After 20 iterations the fit converged.
final sum of squares of residuals : 4.06362e-27
rel. change during last iteration : 0
Exactly as many data points as there are parameters.
In this degenerate case, all errors are zero by definition.
Final set of parameters
=======================
m = 1.35948e-13
b = 4
*******************************************************************************
Sat Oct 7 14:46:29 2023
FIT: data read from './benchmark/easy/stats-7794.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 1.3716051592e+03 0.00e+00 1.02e+01 1.000000e+00 1.000000e+00
5 1.7110904819e+00 -3.66e-08 1.02e-04 1.326173e-01 1.769604e+00
After 5 iterations the fit converged.
final sum of squares of residuals : 1.71109
rel. change during last iteration : -3.66465e-13
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.462478
variance of residuals (reduced chisquare) = WSSR/ndf : 0.213886
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 0.132617 +/- 0.0374 (28.2%)
b = 1.7696 +/- 0.5366 (30.32%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.962 1.000
*******************************************************************************
Sat Oct 7 14:49:51 2023
FIT: data read from './benchmark/easy/stats-8058.txt' using 1:2
format = x:z
#datapoints = 2
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 2.7700175457e+02 0.00e+00 1.05e+01 1.000000e+00 1.000000e+00
BREAK: Singular matrix in Invert_RtR
*******************************************************************************
Sat Oct 7 14:51:13 2023
FIT: data read from './benchmark/medium/stats-8127.txt' using 1:2
format = x:z
#datapoints = 2
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 2.5226676307e+02 0.00e+00 1.01e+01 1.000000e+00 1.000000e+00
BREAK: Singular matrix in Invert_RtR
*******************************************************************************
Sat Oct 7 16:39:13 2023
FIT: data read from './benchmark/easy/stats-34.txt' using 1:2
format = x:z
#datapoints = 30
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 3.7195752550e+02 0.00e+00 3.00e+00 1.000000e+00 1.000000e+00
4 7.0670086113e+01 -5.66e-08 3.00e-04 -3.494468e-01 5.385170e+00
After 4 iterations the fit converged.
final sum of squares of residuals : 70.6701
rel. change during last iteration : -5.65658e-13
degrees of freedom (FIT_NDF) : 28
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.58869
variance of residuals (reduced chisquare) = WSSR/ndf : 2.52393
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = -0.349447 +/- 0.1237 (35.41%)
b = 5.38517 +/- 0.5101 (9.473%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.823 1.000
*******************************************************************************
Sat Oct 7 16:42:49 2023
FIT: data read from './benchmark/medium/stats-320.txt' using 1:2
format = x:z
#datapoints = 20
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 2.3294018743e+02 0.00e+00 4.46e+00 1.000000e+00 1.000000e+00
4 5.3440356726e+00 -3.25e-02 4.46e-04 2.858982e-01 2.086817e+00
After 4 iterations the fit converged.
final sum of squares of residuals : 5.34404
rel. change during last iteration : -3.25197e-07
degrees of freedom (FIT_NDF) : 18
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.544877
variance of residuals (reduced chisquare) = WSSR/ndf : 0.296891
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 0.285898 +/- 0.1419 (49.62%)
b = 2.08682 +/- 0.8833 (42.33%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.990 1.000
*******************************************************************************
Sat Oct 7 16:45:51 2023
FIT: data read from './benchmark/hard/stats-606.txt' using 1:2
format = x:z
#datapoints = 20
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 2.1708445948e+02 0.00e+00 4.42e+00 1.000000e+00 1.000000e+00
4 6.3029262148e+00 -6.80e-04 4.42e-04 3.155035e-01 2.025714e+00
After 4 iterations the fit converged.
final sum of squares of residuals : 6.30293
rel. change during last iteration : -6.80327e-09
degrees of freedom (FIT_NDF) : 18
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.591745
variance of residuals (reduced chisquare) = WSSR/ndf : 0.350163
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 0.315503 +/- 0.07963 (25.24%)
b = 2.02571 +/- 0.4912 (24.25%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.963 1.000
*******************************************************************************
Mon Oct 9 08:35:13 2023
FIT: data read from './benchmark/easy/stats-17804.txt' using 1:2
format = x:z
BREAK: No data to fit
*******************************************************************************
Mon Oct 9 08:35:58 2023
FIT: data read from './benchmark/easy/stats-17974.txt' using 1:2
format = x:z
#datapoints = 5
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 5.0925248596e+00 0.00e+00 1.87e+00 1.000000e+00 1.000000e+00
4 1.4843053908e+00 -2.25e-01 1.87e-04 2.945810e+00 -3.151360e+00
After 4 iterations the fit converged.
final sum of squares of residuals : 1.48431
rel. change during last iteration : -2.24881e-06
degrees of freedom (FIT_NDF) : 3
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.703398
variance of residuals (reduced chisquare) = WSSR/ndf : 0.494768
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 2.94581 +/- 0.9751 (33.1%)
b = -3.15136 +/- 2.388 (75.78%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.991 1.000
*******************************************************************************
Mon Oct 9 08:40:27 2023
FIT: data read from './benchmark/easy/stats-18655.txt' using 1:2
format = x:z
#datapoints = 40
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 3.9186974369e+01 0.00e+00 1.81e+00 1.000000e+00 1.000000e+00
3 3.3252496963e+01 -1.23e-02 1.81e-03 1.050654e+00 1.269805e+00
After 3 iterations the fit converged.
final sum of squares of residuals : 33.2525
rel. change during last iteration : -1.22554e-07
degrees of freedom (FIT_NDF) : 38
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.935449
variance of residuals (reduced chisquare) = WSSR/ndf : 0.875066
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 1.05065 +/- 0.2001 (19.05%)
b = 1.2698 +/- 0.4723 (37.2%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.950 1.000
*******************************************************************************
Mon Oct 9 08:45:55 2023
FIT: data read from './benchmark/easy/stats-20142.txt' using 1:2
format = x:z
#datapoints = 40
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 5.3938122718e+01 0.00e+00 1.88e+00 1.000000e+00 1.000000e+00
3 4.2839306051e+01 -3.80e-02 1.88e-03 1.103008e+00 1.276526e+00
After 3 iterations the fit converged.
final sum of squares of residuals : 42.8393
rel. change during last iteration : -3.7975e-07
degrees of freedom (FIT_NDF) : 38
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.06177
variance of residuals (reduced chisquare) = WSSR/ndf : 1.12735
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 1.10301 +/- 0.3137 (28.44%)
b = 1.27653 +/- 0.7718 (60.46%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.976 1.000
*******************************************************************************
Mon Oct 9 09:06:23 2023
FIT: data read from './benchmark/easy/stats-24031.txt' using 1:2
format = x:z
#datapoints = 40
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 3.5339484360e+02 0.00e+00 3.81e+00 1.000000e+00 1.000000e+00
4 4.8578193452e+01 -3.22e-06 3.81e-04 4.597508e-01 1.097159e+00
After 4 iterations the fit converged.
final sum of squares of residuals : 48.5782
rel. change during last iteration : -3.22376e-11
degrees of freedom (FIT_NDF) : 38
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.13065
variance of residuals (reduced chisquare) = WSSR/ndf : 1.27837
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 0.459751 +/- 0.2232 (48.56%)
b = 1.09716 +/- 1.18 (107.6%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.988 1.000
*******************************************************************************
Mon Oct 9 09:12:07 2023
FIT: data read from './benchmark/easy/stats-26884.txt' using 1:2
format = x:z
#datapoints = 40
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 3.8674872984e+02 0.00e+00 3.81e+00 1.000000e+00 1.000000e+00
5 4.2981793065e+01 -5.55e-08 3.81e-05 -2.073526e+00 1.442782e+01
After 5 iterations the fit converged.
final sum of squares of residuals : 42.9818
rel. change during last iteration : -5.55119e-13
degrees of freedom (FIT_NDF) : 38
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.06353
variance of residuals (reduced chisquare) = WSSR/ndf : 1.1311
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = -2.07353 +/- 0.6118 (29.5%)
b = 14.4278 +/- 3.236 (22.43%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.999 1.000
*******************************************************************************
Mon Oct 9 09:54:13 2023
FIT: data read from './benchmark/diabolical/stats-35904.txt' using 1:2
format = x:z
#datapoints = 40
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 3.1658036471e+02 0.00e+00 3.78e+00 1.000000e+00 1.000000e+00
4 2.5342355613e+01 -6.15e-01 3.78e-04 1.575034e+00 -4.707957e+00
After 4 iterations the fit converged.
final sum of squares of residuals : 25.3424
rel. change during last iteration : -6.14834e-06
degrees of freedom (FIT_NDF) : 38
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.816642
variance of residuals (reduced chisquare) = WSSR/ndf : 0.666904
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 1.57503 +/- 0.4397 (27.92%)
b = -4.70796 +/- 2.309 (49.04%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.998 1.000
*******************************************************************************
Mon Oct 16 08:45:31 2023
FIT: data read from './benchmark/easy/stats-8819.txt' using 1:2
format = x:z
#datapoints = 10
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 1.3195350106e+01 0.00e+00 1.79e+00 1.000000e+00 1.000000e+00
4 9.4927257214e+00 -3.44e-06 1.79e-04 1.797247e+00 -5.650371e-01
After 4 iterations the fit converged.
final sum of squares of residuals : 9.49273
rel. change during last iteration : -3.44075e-11
degrees of freedom (FIT_NDF) : 8
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.08931
variance of residuals (reduced chisquare) = WSSR/ndf : 1.18659
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 1.79725 +/- 0.4761 (26.49%)
b = -0.565037 +/- 1.105 (195.6%)
correlation matrix of the fit parameters:
m b
m 1.000
b -0.950 1.000
*******************************************************************************
Mon Oct 16 08:48:37 2023
FIT: data read from './benchmark/easy/stats-9640.txt' using 1:2
format = x:z
#datapoints = 5
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 4.3935659563e+00 0.00e+00 1.97e+00 1.000000e+00 1.000000e+00
5 1.1480828470e+00 -2.13e-06 1.97e-05 1.504191e+00 4.965356e-01
After 5 iterations the fit converged.
final sum of squares of residuals : 1.14808
rel. change during last iteration : -2.13395e-11
degrees of freedom (FIT_NDF) : 3
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.618623
variance of residuals (reduced chisquare) = WSSR/ndf : 0.382694
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = 1.50419 +/- 4.084 (271.5%)
b = 0.496536 +/- 10.6 (2135%)
correlation matrix of the fit parameters:
m b
m 1.000
b -1.000 1.000
*******************************************************************************
Mon Oct 16 08:58:07 2023
FIT: data read from './benchmark/easy/stats-11483.txt' using 1:2
format = x:z
#datapoints = 4
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 2.8152387624e+00 0.00e+00 2.02e+00 1.000000e+00 1.000000e+00
5 7.8288408735e-01 -3.66e-03 2.02e-05 -6.824464e+00 2.222957e+01
After 5 iterations the fit converged.
final sum of squares of residuals : 0.782884
rel. change during last iteration : -3.65863e-08
degrees of freedom (FIT_NDF) : 2
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.625653
variance of residuals (reduced chisquare) = WSSR/ndf : 0.391442
Final set of parameters Asymptotic Standard Error
======================= ==========================
m = -6.82446 +/- 3.87 (56.71%)
b = 22.2296 +/- 10.34 (46.53%)
correlation matrix of the fit parameters:
m b
m 1.000
b -1.000 1.000
*******************************************************************************
Mon Oct 16 08:58:35 2023
FIT: data read from './benchmark/easy/stats-11672.txt' using 1:2
format = x:z
#datapoints = 4
residuals are weighted equally (unit weight)
function used for fitting: f(x)
f(x) = m*x + b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda m b
0 2.1726750603e+00 0.00e+00 2.00e+00 1.000000e+00 1.000000e+00
5 9.3992332530e-01 -7.99e-04 2.00e-05 6.071146e+00 -1.208175e+01
After 5 iterations the fit converged.
final sum of squares of residuals : 0.939923
rel. change during last iteration : -7.99415e-09
degrees of freedom (FIT_NDF) : 2
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.685537
variance of residuals (reduced chisquare) = WSSR/ndf : 0.469962