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DataFit/DataFitX Nonlinear Regression Results Verification   
NIST Datasets - High level of difficulty
(Graphs produced with DataFit)

DataFit/DataFitX  Lower Difficulty Datasets  Average Difficulty Datasets

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Dataset Name: MGH09
Model: Y = B1*(x^2+x*B2) / (x^2+x*B3+B4)
11 Observations
4 Parameters
NIST Certified Values Calculated Values
Parameter Standard Error Parameter Standard Error
B1=1.928069345E-01
B2=1.912823287E-01
B3=1.230565069E-01
B4=1.360623306E-01
1.143531222E-02
1.963322091E-01
8.084203123E-02
9.002554230E-02
B1=1.928069343E-01
B2=1.912823353E-01
B3=1.230565082E-01
B4=1.360623337E-01
1.143531232E-02
1.963322141E-01
8.084203274E-02
9.002554418E-02
Residual Sum of Squares = 3.0750560385E-04
Residual Standard Dev. = 6.6279236551E-03
Residual Sum of Squares = 3.0750560385-04
Residual Standard Dev. = 6.6279236551E-03

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Dataset Name: MGH10
Model: Y = B1 * exp(B2/(x+B3))
16 Observations
3 Parameters
NIST Certified Values Calculated Values
Parameter Standard Error Parameter Standard Error
B1=5.6096364710E-03
B2=6.1813463463E+03
B3=3.4522363462E+02
1.5687892471E-04
2.3309021107E+01
7.8486103508E-01
B1=5.609636474E-03
B2=6.181346346E+03
B3=3.452236346E+02
1.568789304E-04
2.330902196E+01
7.848610639E-01
Residual Sum of Squares = 8.7945855171E+01
Residual Standard Dev. = 2.6009740065E+00
Residual Sum of Squares = 8.7945855171E+01
Residual Standard Dev. = 2.6009740065E+00

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Dataset Name: Bennett5
Model: Y = B1 * (B2+x)^(-1/B3)
154 Observations
3 Parameters
NIST Certified Values Calculated Values
Parameter Standard Error Parameter Standard Error
B1=-2.5235058043E+03
B2=4.6736564644E+01
B3=9.3218483193E-01
2.9715175411E+02
1.2448871856E+00
2.0272299378E-02
B1=-2.523505671E+03
B2=4.673656408E+01
B3=9.32184841E-01
2.971517689E+02
1.244887316E+00
2.027230189E-02
Residual Sum of Squares = 5.2404744073E-04
Residual Standard Dev. = 1.8629312528E-03
Residual Sum of Squares = 5.2404744073E-04
Residual Standard Dev. = 1.8629312528E-03

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Dataset Name: BoxBOD
Model: Y = B1*(1-exp(-B2*x))
6 Observations
2 Parameters
NIST Certified Values Calculated Values
Parameter Standard Error Parameter Standard Error
B1=2.1380940889E+02
B2=5.4723748542E-01
1.2354515176E+01
1.0455993237E-01
B1=2.13809409E+02
B2=5.472374837E+02
1.23545152E+01
1.04559932E-01
Residual Sum of Squares = 1.1680088766E+03
Residual Standard Dev. = 1.7088072423E+01
Residual Sum of Squares = 1.1680088766E+03
Residual Standard Dev. = 1.7088072423E+01

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Dataset Name: Eckerle4
Model: Y = (B1/B2) * exp(-0.5*((x-B3)/B2)^2)
35 Observations
3 Parameters
NIST Certified Values Calculated Values
Parameter Standard Error Parameter Standard Error
B1=1.5543827178E+00
B2=4.0888321754E+00
B3=4.5154121844E+02
1.5408051163E-02
4.6803020753E-02
4.6800518816E-02
B1=1.554382718E+00
B2=4.088832175E+00
B3=4.515412184E+02
1.540805116E-02
4.680302075E-02
4.680051882E-02
Residual Sum of Squares = 1.4635887487E-03
Residual Standard Dev. = 6.7629245447E-03
Residual Sum of Squares = 1.4635887487E-03
Residual Standard Dev. = 6.7629245447E-03

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Dataset Name: Ratkowsky2
Model: Y = B1 / (1+exp(B2-B3*x))
9 Observations
3 Parameters
NIST Certified Values Calculated Values
Parameter Standard Error Parameter Standard Error
B1=7.2462237576E+01
B2=2.6180768402E+00
B3=6.7359200066E-02
1.7340283401E+00
8.8295217536E-02
3.4465663377E-03
B1=7.246223758E+01
B2=2.61807684E+00
B3=6.735920006E-02
1.73402834E+00
8.829521753E-02
3.446566337E-03
Residual Sum of Squares = 8.0565229338E+00
Residual Standard Dev. = 1.1587725499E+00
Residual Sum of Squares = 8.0565229338E+00
Residual Standard Dev. = 1.1587725499E+00

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Dataset Name: Ratkowsky3
Model: Y = B1 / ((1+exp(B2-B3*x))^(1/B4))
15 Observations
4 Parameters
NIST Certified Values Calculated Values
Parameter Standard Error Parameter Standard Error
B1=6.9964151270E+02
B2=5.2771253025E+00
B3=7.5962938329E-01
B4=1.2792483859E+00
1.6302297817E+01
2.0828735829E+00
1.9566123451E-01
6.8761936385E-01
B1=6.996415127E+02
B2=5.277125301E+00
B3=7.596293832E-01
B4=1.279248385E+00
1.630229781E+01
2.082873582E+00
1.956612344E-01
6.876193635E-01
Residual Sum of Squares = 8.7864049080E+03
Residual Standard Dev. = 2.8262414662E+01
Residual Sum of Squares = 8.7864049080E+03
Residual Standard Dev. = 2.8262414662E+01

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Dataset Name: Thurber
Model: Y = (B1 + B2*x + B3*x^2 + B4*x^3) / (1 + B5*x + B6*x^2 + B7*x^3)
37 Observations
7 Parameters
NIST Certified Values Calculated Values
Parameter Standard Error Parameter Standard Error
B1=1.2881396800E+03
B2=1.4910792535E+03
B3=5.8323836877E+02
B4=7.5416644291E+01
B5=9.6629502864E-01
B6=3.9797285797E-01
B7=4.9727297349E-02
4.6647963344E+00
3.9571156086E+01
2.8698696102E+01
5.5675370270E+00
3.1333340687E-02
1.4984928198E-02
6.5842344623E-03
B1=1.28813968E+03
B2=1.491079267E+03
B3=5.832383781E+02
B4=7.541664612E+01
B5=9.662950377E-01
B6=3.979728621E-01
B7=4.972730005E-02
4.664796324E+00
3.957114667E+01
2.869868928E+01
5.56753567E+00
3.133333429E-02
1.498492512E-02
6.584232857E-03
Residual Sum of Squares = 5.6427082397E+03
Residual Standard Dev. = 1.3714600784E+01
Residual Sum of Squares = 5.6427082397E+03
Residual Standard Dev. = 1.3714600784E+01

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DataFit/DataFitX  Lower Difficulty Datasets  Average Difficulty Datasets

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