MEAN VALUE ESTIMATION FROM DIGITAL COMPUTER SIMULATION,

Abstract

Terminating and non-terminating stochastic processes are studied. If digital simulation is used, either a time-slicing or an event-sequencing technique may be used to obtain an estimate of some measure (mean value in our case) of system performance. We consider the variance of the estimate to be the basic measure for determining the goodness of the estimate. Three points are examined: (1) unbiasedness of the estimate, (2) efficiency of the estimate, and (3) variance reduction techniques. For the nonterminating case a large class of steady state processes having a negative exponential covariance function is studied and curves and specific examples are derived. Replication is shown to be generally superior to increasing the length of a run. For the terminating case, a general expression for efficiency is derived and again replication is shown to be the superior variance reduction technique. All results are equally valid for discrete or continuous processes. (Author)

Document Details

Document Type
Technical Report
Publication Date
Mar 22, 1965
Accession Number
AD0613272

Entities

People

  • A. V. Gafarian
  • C. J. Ancker Jr.

Organizations

  • System Development Corporation

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Computer Simulations
  • Computers
  • Control Simulators
  • Covariance
  • Digital Computers
  • Efficiency
  • Simulations
  • Simulators
  • Steady State
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Mathematical Modeling and Probability Theory.
  • Regression Analysis.
  • Statistical inference.