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Linear Fitter

What is fitting? Suppose that you have a table of numbers, Yi and Xi,  i=0..n. Then suppose that you have model representation for these numeric Y(X) data: Y=f(X,pj), j=1..m, and you want to find numeric values of pj that made table-defined curve Yi( Xi) and model curve Y=f(X,pj) most similar. This process is known as fitting. If model function has linear dependence on fitting parameters, this can be treated as linear fitting, otherwise you will have non-linear fitting problem.

Linear fitting has more limited applications than NLSF. However, it is much more fast and straightforward and does not require initial parameter evaluations. This feature makes it more convenient for various automatic fitting routines (see IDMApplication interface for more details). Unfortunately linear fitting method has serious restriction: you can fit only several predefined model functions (or function classes).

How to use Linear fitter? First you should plot data to be processed (this tool works only with active plot serie). Then make plot active and select Process|Linear Fit menu item to display Linear Fitter window. You will see your curve on the separate plot. Just select desirable fitting expression from the list and click "Fit" button to create and show best fit curve.

In DM2000 you have a wide set of options that allows you to have full control over the fitting process.

Notice: if active serie (curve to be fitted) has nonempty X, Y expressions,  fit calculation algorithm will take these expressions into account. In another words, transformed curve will be fitted. However, axis expressions will be simply ignored (and you get warning message).