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Communications in Statistics - Simulation and Computation Volume 19, 1990 - Issue 3
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Original Articles

A comparison of the performances of procedures for selecting the normal population having the largest mean when the populations have a common unknown variance

Robert E. Bechhofer School of Operations Research and Industrial Engineering, Cornell University, Upson Hall, Ithaca, NY 14853
,
David M. Goldsman School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332
,
Charles W. Dunnett Department of Mathematics and Statistics, McMaster University Hamilton, Ontario, L8S-4K1, Canada
&
Mark Hartmann Department of Operations Research, University of North Carolina, Chapel Hill, NC 27599
Pages 971-1006 | Published online: 27 Jun 2007

Citations (11)

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Mark Hartmann. (1991) An improvement on paulson's procedure for selecting the poprlation with the largest mean from k normal populations with a common unknown variance. Sequential Analysis 10:1-2, pages 1-16.
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Articles from other publishers (10)

Dmytro Pukhkaiev, Yevhenii Semendiak & Uwe Asmann. (2020) To Measure or not to Measure? Adaptive Repetition Management in Parameter Tuning. To Measure or not to Measure? Adaptive Repetition Management in Parameter Tuning.
Ruijing Wu, Shaoxuan Liu & Zhenyang Shi. (2020) Algorithm for Calculating the Initial Sample Size in a Fully Sequential Ranking and Selection Procedure. Asia-Pacific Journal of Operational Research 37:03, pages 2050015.
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Royi Jacobovic & Or Zuk. (2017) On the asymptotic efficiency of selection procedures for independent Gaussian populations. Electronic Journal of Statistics 11:2.
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A.E. Eiben & S.K. Smit. (2011) Parameter tuning for configuring and analyzing evolutionary algorithms. Swarm and Evolutionary Computation 1:1, pages 19-31.
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A. E. Eiben & S. K. Smit. 2012. Autonomous Search. Autonomous Search 15 36 .
Juta Pichitlamken, Barry L. Nelson & L. Jeff Hong. (2006) A sequential procedure for neighborhood selection-of-the-best in optimization via simulation. European Journal of Operational Research 173:1, pages 283-298.
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Barry L. Nelson, Julie Swann, David Goldsman & Wheyming Song. (2001) Simple Procedures for Selecting the Best Simulated System When the Number of Alternatives is Large. Operations Research 49:6, pages 950-963.
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Seong-Hee Kim & Barry L. Nelson. (2001) A fully sequential procedure for indifference-zone selection in simulation. ACM Transactions on Modeling and Computer Simulation 11:3, pages 251-273.
Crossref
J. Pichitlamken & B.L. Nelson. (2001) Selection-of-the-best procedures for optimization via simulation. Selection-of-the-best procedures for optimization via simulation.
D. Goldsman, B.L. Nelson & B. Schmeiser. (1991) Methods for selecting the best system (for simulation). Methods for selecting the best system (for simulation).

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