FindGraph provides an easy way to determine the best-fit parameters for
linear regression model.
The form of the general least-squares linear regression model is:
where fj(X) are any arbitrary functions of X.
In regression modeling, the term 'linear'
means that the models dependence on its parameters Aj is linear. The functions
fj(X) may be nonlinear.
In FindGraph, linear regression model is linear combination of
Polynomial, Rational, Logarithmic, Exponential, and Fourier functions fjk(X).
The parameters Aj are estimated by the method of least-squares
to minimize the difference between the model and data.
The Wizard of Approximation will help you to find the best equation
and get a report of the results in seconds.
There is feature to apply robust fitting instead linear regression.
After regression we exclude points out of 1.5*stdErr interval, and find regression line again.
There is feature to apply regularization, mainly Forward Stagewise Linear Regression algorithm to prevent overfitting.
FindGraph provides automatic logging of all curve-fit analysis.
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