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http://dx.doi.org/10.9709/JKSS.2012.21.3.011

Output Data Analysis of Simulation: A Review  

Chang, Byeong-Yun (아주대학교 경영학부)
Publication Information
Journal of the Korea Society for Simulation / v.21, no.3, 2012 , pp. 11-16 More about this Journal
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 ${\mu}$ in terminating and non-terminating simulation cases. We, then, explore the estimation techniques for $f({\mu})$, where the function $f({\bullet})$ is a nonlinear that is continuously differentiable in a neighborhood of ${\mu}$ with $f.
Keywords
Simulation; Output Data Analysis; Confidence Interval; Nonlinear Function;
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