Statistical Analysis of Discrete-Event Simulations.
CONTROL ANALYSIS CORP PALO ALTO CALIF
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The paper surveys past and ongoing work by the authors in statistical analysis of simulations. An earlier developed technique for analyzing simulations of GIGS queues and Markov chains is shown to apply to discrete-event simulations which can be modeled as regenerative processes. It is possible to address questions of simulation run duration and of starting and stopping simulations because of the existence of a random grouping of observations which produces independent identically distributed blocks in the course of the simulation. This grouping allows one to obtain confidence intervals for a general function of the steady-state distribution of the process being simulated. The technique is illustrated with a simulation of a retail inventory distribution system. Modified author abstract
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