About Curve Fitting Functions
When you perform curve fitting, you fit a single function, in a least-squares sense, through all data points. This method contrast with interpolation, where piece-wise functions are fitted through adjacent data points.
To further analyze your data, or determine the suitability of the chosen regression, you may wish to apply other statistics functions for data analysis.
Linear and Median-Median Regression
• medfit—Median-median line regression for data
Polynomial and Rational Function Regression
• loess—Localized polynomial regression
Nonlinear Regression
• genfit—Least-squares nonlinear regression for arbitrary fit functions
• expfit—Least-squares exponential regression
• lgsfit—Least-squares logistic curve regression
• pwrfit—Least-squares power curve regression
• sinfit—Least-squares sinusoidal regression
If you want to include additional information about the data or the parameters for any of the above fits, such as standard deviation in the data, bounds on the parameters, or constraint functions, you should use the
LeastSquaresFit function to do the calculation in a more detailed way.
Other Functions
• linfit—Least-squares regression for an arbitrary linear combination of functions