A two-stage procedure for selecting the largest normal mean whose first stage selects a bounded random number of populations

DOI10.1016/0378-3758(92)90026-OzbMath0759.62013OpenAlexW2075515845WikidataQ127704133 ScholiaQ127704133MaRDI QIDQ1194011

Maika Behaxeteguy Heffernan, Thomas J. Santner

Publication date: 27 September 1992

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(92)90026-o

zbMATH Keywords

PCSlower boundindifference zoneoptimal design problemnormal populationsscreeningtwo-stage procedurelargest meanprobability of correct selectionunknown meanstwo-stage proceduresapproximate conservative solutioncommon known variancerestricted subset selectionsingle-stage procedure

Mathematics Subject Classification ID

Design of statistical experiments (62K99) Statistical ranking and selection procedures (62F07)

Related Items (3)

On the selection probabilities of two-stage decision procedures ⋮ Selecting a Good Stochastic System for the Large Number of Alternatives ⋮ Selecting the best simulated system with weighted control-variate estimators

Cites Work

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• Selection from multivariate normal populations
• A two-sample procedure for selecting the population with the largest mean from k normal populations
• On a conjecture concerning the least favorable configuration of a two-stage selection procedure
• A two-stage minimax procedure with screening for selecting the largest normal mean (ii): an improved pcs lower bound and associated tables
• Some Fixed-Sample Ranking and Selection Problems
• A Single-Sample Multiple Decision Procedure for Ranking Means of Normal Populations with known Variances
• SOME PROBLEMS OF OPTIMUM SAMPLING

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