MATLAB Implementation of Monte Carlo Method

The Monte Carlo program is a mathematically-based computational tool primarily designed for simulating uncertainties and providing decision support. It employs random sampling techniques to model various scenarios, enabling users to gain better insights into complex problems and make informed decisions. This implementation utilizes MATLAB m-files, which represent a high-level programming language environment offering streamlined debugging and execution capabilities. The program typically involves key functions such as random number generation (using rand or randn), statistical analysis routines, and iterative simulation loops. Through its algorithmic approach of repeated random sampling, the Monte Carlo program not only enhances computational efficiency but also helps users systematically understand and solve probabilistic problems by approximating solutions through statistical methods. The m-file structure allows for modular code organization, where separate functions can handle specific tasks like probability distribution modeling, result aggregation, and convergence testing.