Global Fitting in Origin
 
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Origin: Global Curve Fitting

There may be situations where you would like to fit multiple datasets with the same fitting function. It may also be the case that the datasets you wish to fit share one or more parameters in the common fitting function. In Origin, we call this type of fitting operation Global Fitting, borrowing from general programming lexicon in which a global variable is one that can be seen by all subroutines, functions, classes, and methods.

Origin supports global fitting wherein each parameter in the common fitting function can optionally be shared by all datasets, or can be kept independent. If a parameter is shared, the fitting procedure will yield one best-fit value for that parameter for all datasets. If a parameter is not shared, the fitting procedure will yield a unique value for each dataset.

Global Fitting in Origin, key points:

  • Multiple datasets are fitted with one model simultaneously.
  • Fit parameters are optionally shared between the datasets.
    • For each shared (global) parameter, one best-fit value is estimated from all of the datasets that are fitted.
    • For each non-shared (local) parameter, a unique best-fit value is generated for individual dataset that is fitted.
  • Other options such as constraints and weighting are also available when you choose to perform Global Fitting.

Global fitting example

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