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Contents -> Fitting -> fc set fit criteria and fit options -> Convergence and statistical parameters
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| C-PLOT Manual | |
12.5.5. - Convergence and statistical parametersFinally, you are asked if you wish to change the statistical criteria. These variables are concerned with certain details of the fitting algorithm and don't normally need to be altered. The first variable you can change is the starting value of the Marquardt algorithm compromise parameter, lambda. This parameter controls how much of the gradient search versus how much of parabolic expansion is used to determine the direction of the search. The larger lambda is, the more the algorithm uses the gradient search. The next variable is the minimum value allowed for lambda. It won't be permitted to go lower than the value selected here. When the program calculates the derivative of the fitting function numerically with respect to a fitted parameter bi, it uses values of the function at bi and at (1 +  )bi.
You can enter here a value to use for .
The default
value is 0.00001.
The next two values,  and  , are important in deciding
at what point the fit has converged.
They are used in a convergence
test that is satisfied if for each parameter bi
and parameter
increment bi,
|The parameter increments are the changes in the value of each parameter from the prior iteration. mostly functions to prevent division
by zero.
The default value for both is 0.001.
The parameter  measures the angle between the direction of
steepest descent of the  2 hypersurface and the direction
of the current iteration.
When falls below the critical
value set here, the course of the fitting algorithm changes as described
below under
fi. The value of the matrix singularity variable lets you adjust how small the determinant of the parameter correlation matrix can be before giving up on the fit. The last two variables, ff and tt, are concerned only with the quantities on the final printout obtained with the fp command.
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