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Regression Summary
Levenberg-Marquardt Algorithm
sum of squares | 0.0441438 |
mean square | 0.00882877 |
r.m.s. deviation | 0.0939615 |
relative r.m.s. (%) | 0.536004 |
R2 ... (a) | 0.998813 |
R2adj ... (a) | 0.998813 |
log(determinant) | -1.22138 |
data points | 5 |
optimized parameters | 2 |
iterations | 13 |
subiterations | 0 |
elapsed time (sec) | 0.032 |
error status | 1 |
error message | |
(a)
WARNING: R2 is not a suitable measure of goodness-of-fit for nonlinear models.
R2 is listed here only for compatibility with other software packages.
Please do not misuse R2 to "justify" any nonlinear models generated by DynaFit.
Progress of Regression Analysis
Evolution of best-fit parameter values: [TAB-DELIMITED TEXT]Trust-Region Algorithm
sum of squares | 0.0441438 |
mean square | 0.00882877 |
r.m.s. deviation | 0.0939615 |
relative r.m.s. (%) | 0.536004 |
R2 ... (a) | 0.999728 |
R2adj ... (a) | 0.999637 |
log(determinant) | 0 |
data points | 5 |
optimized parameters | 2 |
iterations | 10 |
elapsed time (sec) | 0 |
(a)
WARNING: R2 is not a suitable measure of goodness-of-fit for nonlinear models.
R2 is listed here only for compatibility with other software packages.
Please do not misuse R2 to "justify" any nonlinear models generated by DynaFit.
Progress of Regression Analysis
Evolution of best-fit parameter values: [TAB-DELIMITED TEXT]
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