The term "Monte Carlo simulation" refers to a statistical method where random samples are used to analyze quantitative models and solve complex problems. It is commonly used to assess uncertainties and risks across various scenarios by generating and analyzing random data values multiple times.
Typical software functions in the area of "Monte Carlo simulation" include:
Random Data Generation: Generating random data values according to defined distributions and parameters.
Model Building: Creating quantitative models that describe the structure and variables of the system under analysis.
Simulation: Running the Monte Carlo simulation to perform multiple iterations of model calculations.
Result Analysis: Analyzing simulation results to assess risks, uncertainties, and potential outcomes.
Visualization: Presenting results through graphs, charts, and reports to support decision-making.
Scenario Analysis: Examining different scenarios and their impacts on simulation results.