Statistical Analysis of Simulation Output Data

4577 Words19 Pages
Proceedings of the 2010 Winter Simulation Conference B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yücesan, eds. STATISTICAL ANALYSIS OF SIMULATION OUTPUT DATA: THE PRACTICAL STATE OF THE ART Averill M. Law Averill M. Law & Associates 4729 East Sunrise Drive, #462 Tucson, AZ 85718, USA ABSTRACT One of the most important but neglected aspects of a simulation study is the proper design and analysis of simulation experiments. In this tutorial we give a state-of-the-art presentation of what the practitioner really needs to know to be successful. We will discuss how to choose the simulation run length, the warmup-period duration (if any), and the required number of model replications (each using different…show more content…
However, note that 1 2 , ,..., i i ni y y y (from the ith column) are IID observations of the random variable Yi , for i m 1,2,..., . More generally,                      the same (joint) distribution. This independence across runs is the key to relatively simple output-data analysis that is discussed in later sections of this paper. Then, roughly speaking, the goal of output-data analysis is to use the observations ji y (i !"$%m; j !"$%n) to draw inferences about characteristics of the random variables Y Y Ym , , , 1 2  . Example 2. Consider a bank with five tellers and one queue, which opens its doors at 9 A.M., closes its doors at 5 P.M., but stays open until all customers in the bank at 5 P.M. have been served. Assume that customers arrive with IID exponential interarrival times with mean 1 minute, that service times are IID exponential random variables with mean 4 minutes, and that customers are served in a first-in, first-out (FIFO) manner. Table 1 shows two typical output statistics from 5 independent replications of the bank, assuming that no customers are present initially. Note that results from dif-     *   +         / 
Get Access