A Conceptual Framework for Research in the Analysis of Simulation Output.

An important part of a simulation study is the analysis of simulation output for the purpose of making inferences about properties of the process being simulated. Fundamental to much of this analysis is the building of a confidence interval on the mean value of a key output variable of interest. This procedure is complicated by the possible presence of serial correlation in the output, which makes it difficult to estimate the variability in the estimator of the process mean. Although some research has been devoted to estimating this variability, additional research must be directed toward developing reliable confidence interval procedures and making the practitioner's selection of an appropriate procedure relatively straightforward. This paper provides a conceptual framework for research in the analysis of simulation output, focusing in particular on confidence interval methodology. The characteristics of confidence interval procedures, theoretical output processes, and processes of practical interest to simulation practitioners are discussed, and their relationships with one another spelled out. Standard measures of effectiveness applicable to proposed confidence interval procedures are introduced, and the application of these measures to two previously suggested confidence interval procedures is illustrated. [ABSTRACT FROM AUTHOR]