MATLAB Code Implementation for Poisson Distribution Simulation

This MATLAB code implements Poisson distribution simulation with integrated validation procedures. The Poisson distribution is a fundamental discrete probability distribution in statistics that models the number of events occurring within a fixed time interval, assuming events happen independently with a known average rate. This distribution finds extensive applications in communication systems, traffic flow modeling, population statistics, and various engineering fields. The implementation allows users to input the desired lambda parameter (expected event rate) and generates corresponding Poisson-distributed random variables. The simulation results are displayed on-screen and simultaneously saved to output files for further analysis. The validation module employs multiple test cases with different parameter values to verify code accuracy, comparing simulated results against theoretical probability distributions to ensure reliability. Key implementation features include: - Utilization of MATLAB's built-in random number generation functions optimized for Poisson distribution - Algorithm implementation based on the inverse transform method or acceptance-rejection technique for efficient sampling - Statistical validation through chi-square goodness-of-fit tests comparing empirical and theoretical distributions - Comprehensive code comments and documentation facilitating user understanding and customization - Modular structure allowing easy integration with larger simulation frameworks This enhanced version provides robust simulation capabilities suitable for both educational and research purposes. For technical inquiries or enhancement suggestions, please contact our development team.