Multiple comparisons with a standard using false discovery rates
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Authors
Singham, Dashi I.
Szechtman, Roberto
Subjects
Advisors
Date of Issue
2016
Date
Publisher
Association for Computing Machinery (ACM)
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Abstract
We introduce a new framework for performing multiple comparisons with a standard when simulation models are available to estimate the performance of many different systems. In this setting, a large proportion of the systems have mean performance from some known null distribution, and the goal is to select alternative systems whose means are different from that of the null distribution. We employ empirical Bayes ideas to achieve a bound on the false discovery rate (proportion of selected systems from the null distribution) and a desired probability an alternate type system is selected.
Type
Conference Paper
Description
Refereed Conference Paper
Series/Report No
Department
Operations Research (OR)
Organization
Naval Postgraduate School (U.S.)
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NPS Report Number
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Citation
D.I. Singham, R. Szechtman, "Multiple comparisons with a standard using false discovery rates." Proceedings of the 2016 Winter Simulation Conference. IEEE Press, (2016), 11 p..
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Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.