Statistical Considerations in Computer Simulation Experiments.

by George S. Fishman

Purchase

Purchase Print Copy

 FormatList Price Price
Add to Cart Paperback7 pages $20.00 $16.00 20% Web Discount

A tutorial given at a symposium on the interface between computer science and statistics sponsored by UCLA Extension, The American Statistical Association (Southern California Chapter), and the Association for Computing Machinery (Los Angeles Chapter), February 1, 1967. This paper describes some fundamental statistical problems that should be recognized at all stages of a system simulation that is, or contains, a queueing network, such as inventory models and job shop manufacturing facilities. Such a simulation is the generation of stochastic processes by Monte Carlo methods. While simulation languages such as SIMSCRIPT and GPSS have been developed and refined during the past decade, very little work has been done in applying statistical methodology to the analysis of computer simulations. (See also RM-4880, RM-5288.) 7 pp. Ref.

This report is part of the RAND Corporation Paper series. The paper was a product of the RAND Corporation from 1948 to 2003 that captured speeches, memorials, and derivative research, usually prepared on authors' own time and meant to be the scholarly or scientific contribution of individual authors to their professional fields. Papers were less formal than reports and did not require rigorous peer review.

Our mission to help improve policy and decisionmaking through research and analysis is enabled through our core values of quality and objectivity and our unwavering commitment to the highest level of integrity and ethical behavior. To help ensure our research and analysis are rigorous, objective, and nonpartisan, we subject our research publications to a robust and exacting quality-assurance process; avoid both the appearance and reality of financial and other conflicts of interest through staff training, project screening, and a policy of mandatory disclosure; and pursue transparency in our research engagements through our commitment to the open publication of our research findings and recommendations, disclosure of the source of funding of published research, and policies to ensure intellectual independence. For more information, visit www.rand.org/about/research-integrity.

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.