Fit logarithm function
Purpose
Description
Tips
Macro Synopsis
Modules
Related Functions
References
Purpose
Marquardt-Levenberg fitting to logarithmic functions
Description
"Fit logarithm function" performs a nonlinear fitting of the given signal to a logarithmic function of the form
The maximum order is limited to 16. If fitting flags are omitted, Dataplore ® defaults to fit(1) the corresponding values.
Parameters of "Fit logarithm function" are
- the offset, corresponding to
- a flag denoting if the offset is to be fitted (1) or to be held fixed (0)
- the coefficient a
- a flag denoting if a is to be fitted (1) or to be held fixed (0)
- the shift parameter b and
- a flag denoting if b is to be fitted (1) or to be held fixed(0).
If fitting flags are omitted, Dataplore ® defaults to fit(1) the corresponding values.
Tips
In order to achieve satisfying fitting results, try to give start parameters that are not too far away from the expected resulting values. To that end, you can try to successively fit single parameters while holding fixed other parameters whose estimations already seem to be good enough.
Macro Synopsis
y = LogFit(x,offset,a,aflag,b,bflag);
y = LogFit([x,weight],offset,a,aflag,b,bflag);
signal x,y,weight;
int order;
string offset,a,aflag,b,bflag;
Note that x can be a standard or an XY plot signal..
Modules
Statistics
Related Functions
Fit Boltzmann functions, Fit Bradley model, Fit Chapman model, Fit exponential decay functions, Fit Gunary model, Fit Farazdaghi-Harris model, Fit Hill functions, Fit hyperbola functions, Fit logistic functions, Fit Lorentz functions, Fit monomolecular growth model, Fit Nelder model, Fit Pareto functions, Fit polynomial functions, Fit ratio of polynomial functions, Fit Richards growth model, Fit sine functions, Fit damped sine functions, Fit Weibull functions
References
Marquardt [29]