MATLAB Source Code for Data Regression Analysis

This collection contains highly practical MATLAB source code specifically designed for data regression analysis tasks. The code provides comprehensive implementations of regression methodologies, helping users better understand and apply regression analysis techniques computationally. You can utilize these scripts to analyze and compare different regression models—such as linear regression, polynomial regression, or robust regression—to determine the most suitable model for your specific dataset through performance metrics evaluation. The implementations include approaches for parameter estimation using ordinary least squares (OLS) methods, gradient descent optimization, and regularization techniques like Ridge or Lasso regression. Additionally, the code demonstrates various data visualization methods essential for regression analysis, including scatter plots with regression lines, residual analysis plots, and goodness-of-fit visualizations, enabling clearer interpretation of data trends and relationships. These well-documented scripts are particularly valuable for researchers and practitioners seeking to deepen their understanding of regression analysis through hands-on MATLAB implementation.