Next: Splines and Interpolation
Curve Fitting Toolbox supports linear and nonlinear regression.
The toolbox supports over 100 regression models, including:
- Lines and planes
- High order polynomials (up to ninth degree for curves and fifth degree for surfaces)
- Fourier and power series
- Weibull functions
- Rational functions
- Sum of sines
All of these standard regression models include optimized solver parameters and starting conditions to improve fit quality. Alternatively, you can use the Custom Equation option to specify your own regression model.
In the Curve Fitting app you can generate fits based on complicated parametric models by using a drop-down menu. At the command line you can access the same models using intuitive names.
Nonlinear regression using a second-order Fourier series. You can pass the argument “fourier2” to the fit command (top, left) or select a second-order Fourier series in the Fit Editor (top, right).
Surface generated using the Custom Equation option of the Curve Fitting app. You can specify a custom equation or input a MATLAB function.
The regression analysis options in Curve Fitting Toolbox enable you to:
- Choose between two types of robust regression: bisquare or least absolute residual
- Specify starting conditions for the solvers
- Constrain regression coefficients
- Choose Trust-Region or Levenberg-Marquardt algorithms
Adjusting fit options using the Curve Fitting app. You can control the type of robust regression, the choice of optimization solver, and the behavior of the optimization solver with respect to starting conditions and constraints.