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This code will discuss the practical implementation of the curve fitting schemes. The schemes to be explored are least-square fits, polynomial fits,
line interpolation and spline interpolation. Additionally, a nonpolynomial least-square fit will be considered which results in a nonlinear system of equations. This nonlinear system requires additional insight into the problem and sophistication in its solution technique. To begin the data fit process, we first import a relevant data set into the MATLAB environment. To do so, the load command is used. The file linefit.dat is a collection of x and y data values put into a two-column format separated by spaces.
Cite As
Mohamed Abugammar (2026). Data Fitting with MATLAB (https://www.mathworks.com/matlabcentral/fileexchange/71163-data-fitting-with-matlab), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.0.0 (2.34 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0 |
