Fitting curves using least-squares regression in DataScene is performed with the Nonlinear Fit series function. The user can choose one of the built-in model functions or build his/her own custom function in the fit. DataScene’s curve fitting algorithm is very robust – there is no limit to the number of fitting parameters used in the model function of the fit.
Fitting with Built-in Model Functions
DataScene supports five built-in model functions: Exponential, Polynomial, Gaussian, Lorentzian, and Voigt. By analyzing the curve to be fit and the information provided by the user via the Series Fucntion Editor, DataScene automatically estimates the initial values for the fitting parameters and in majority cases this will result in a converged fit without the user’s interference.
Fitting with Arbitrary Custom Functions
In DataScene, the user can build any custom model function with any number of fitting parameters. Adding and editing a new model function is extremely easy with DataScene’s Series Fucntion Editor and its embedded formula editor that contains in-place help for all library functions and constants.
Linear regression is performed in DataScene with the Linear Regression series function. It just takes the user few mouse clicks to have the job done.
If the source curve changes, DataScene will automatically redo the regression without the user’s interaction. This feature takes the burden of recalculation off the user’s shoulder and makes it possible for DataScene to fit real-time data.
Ease of Use
DataScene comes with a user friendly Wizard, as well as tutorials and context-sensitive help. With the Wizard, it takes only few minutes for a new user to learn to fit curves with DataScene.