MATLAB Implementation of AR Algorithm with Code Example

This document presents a complete MATLAB implementation of the Autoregressive (AR) algorithm. The code has been personally developed and rigorously tested in practical applications, demonstrating robust performance across various scenarios. The implementation includes core functions for parameter estimation using methods like Yule-Walker equations or Burg's algorithm, with configurable model order selection. Key features of the code include: - Flexible AR model order specification - Efficient coefficient calculation using matrix operations - Built-in signal preprocessing routines - Comprehensive error handling and validation checks The code structure follows MATLAB best practices, with clear function documentation and examples of usage for time series analysis and spectral estimation applications. Each major function includes comments explaining the mathematical basis and implementation choices. We welcome any questions, suggestions, or constructive feedback regarding this implementation. Valuable insights will be incorporated to further enhance the code's reliability and adaptability for diverse application requirements. Thank you for your interest and contributions.