Output Data Analysis of Simulation: A Review

Abstract

Simulation is the imitation of the operation of a real-world process or system over time. It concerns the study of the operating characteristics of real systems. Typically, a simulation project consists of several steps such as data collection, coding, model verification, model validation, experimental design, output data analysis, and implementation. Among these steps of a simulation study this paper focus on statistical analysis methods of simulation output data. Specially, we explain how to develop confidence interval estimators for mean μ in terminating and non-terminating simulation cases. We, then, explore the estimation techniques for f(μ), where the function f(•) is a nonlinear that is continuously differentiable in a neighborhood of μ with f'(μ) ≠0.