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Barry L. Nelson
Researcher at Northwestern University
Publications - 279
Citations - 15869
Barry L. Nelson is an academic researcher from Northwestern University. The author has contributed to research in topics: Stochastic simulation & Estimator. The author has an hindex of 53, co-authored 272 publications receiving 14815 citations. Previous affiliations of Barry L. Nelson include Lancaster University & Ohio State University.
Papers
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Proceedings Article
Selecting the best system: selecting the best system: theory and methods
Seong-Hee Kim,Barry L. Nelson +1 more
TL;DR: This paper provides an advanced tutorial on the construction of ranking-and-selection procedures for selecting the best simulated system, and the key theoretical results that are used to derive them.
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Modelling and simulating non-stationary arrival processes to facilitate analysis
Barry L. Nelson,Ira Gerhardt +1 more
TL;DR: A method to model and simulate non-stationary, non-renewal arrival processes that depends only on the analyst setting intuitive and easily controllable parameters is introduced, suitable for assessing the impact of non- stationary,non-exponential, and non-independent arrivals on simulated performance when they are suspected.
Proceedings ArticleDOI
Panel: academic perspectives: various ways academics teach simulation: are they all appropriate?
Tayfur Altiok,W. David Kelton,Pierre L'Ecuyer,Barry L. Nelson,Bruce W. Schmeiser,Thomas J. Schriber,Lee W. Schruben,James R. Wilson +7 more
TL;DR: In this article, the authors discuss goals and educational strategies for teaching simulation in academia and how to motivate and empower students to analyze complex problems correctly and to prevent the pitfall of misusing the concept.
Journal ArticleDOI
Virtual Statistics in Simulation via k Nearest Neighbors
TL;DR: In this paper, virtual statistics are defined as estimators of performance measures that are conditional on the occurrence of an event; virtual waiting time of a customer arriving to a queue at time τ0...
Proceedings ArticleDOI
Input modeling when simple models fail
Barry L. Nelson,Marne C. Cario,Chester A. Harris,Stephanie A. Jamison,J. O. Miller,James Steinbugl,Jaehwan Yang,Peter P. Ware +7 more
TL;DR: This tutorial describes input models that are useful when simple models are not, and how to fit these distributions to data.