Selecting and ordering populations: a new statistical methodology
Selecting and ordering populations: a new statistical methodology
Statistics in simulation: How to design for selecting the best alternative
WSC '76 Proceedings of the 76 Bicentennial conference on Winter simulation
Selection in factorial experiments
WSC '77 Proceedings of the 9th conference on Winter simulation - Volume 1
Estimation of the best alternative
WSC '77 Proceedings of the 9th conference on Winter simulation - Volume 1
WSC '77 Proceedings of the 9th conference on Winter simulation - Volume 1
WSC '77 Proceedings of the 9th conference on Winter simulation - Volume 1
Nonparametric selection procedures applied to state traffic fatality rates
WSC '77 Proceedings of the 9th conference on Winter simulation - Volume 1
Selecting the population with the smallest dispersion in a nonparametric setting
WSC '77 Proceedings of the 9th conference on Winter simulation - Volume 1
Design and analysis of simulation experiments
WSC '78 Proceedings of the 10th conference on Winter simulation - Volume 1
Multivariate ranking and selection without reduction to a univariate problem
WSC '78 Proceedings of the 10th conference on Winter simulation - Volume 1
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“Ranking and selection” procedures were developed for use in situations where the experimenter's goal is to “select the best” (selection) or to “rank competing alternatives” (ranking). These are typical goals when a simulation study is performed, often in order to select that one of several procedures (for running a real-world system) which is best (with regard to a specified criterion of goodness). Therefore these procedures have become a standard analysis method in simulation work in recent years (e.g., see the references in (8)). In this paper we: review some of the selection procedures most often found useful in design and analysis of simulation experiments; discuss some other important procedures and related problems; and state some unsolved statistical problems of importance in simulation work.