Monte Carlo simulation is a method for exploring the sensitivity of a complex system by varying parameters within statistical constraints. These systems can include financial, physical, and mathematical models that are simulated in a loop, with statistical uncertainty between simulations. The results from the simulation are analyzed to determine the characteristics of the system.
You can perform Monte Carlo analysis with MATLAB and Simulink. MATLAB and Statistics Toolbox let you vary uncertain parameters for your model. In Simulink, you can create dynamic simulations and alter parameters with statistical uncertainty. With both MATLAB and Simulink you can:
See also: formal verification, financial engineering, random number, system verification and validation, Monte Carlo simulation in computational finance, parameter estimation, load forecasting, modeling and simulation