UNIPHIZ Lab software

Software FindGraph Regression

Least-squares linear regression

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Simplify the task of curve fitting and regression analysis

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: General least-squares linear regression model

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.

  Linear regression master and fitting log window

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.

Read more about:

Digitizing Digitizing
Graphing Graphing
Curve fitting Curve fitting
Best-fit Best-fit equation
Closed curves Closed curves
Rationals Empirical models
Library Library
Analysis Analysis
Tools Tools
Filters Filters
Convolution Convolution
Extract of periodic signals Periodic signals
Procrustes analysis Procrustes analysis
Multi-peak fitting Multi-peak fitting
SSA forecasting SSA forecasting




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