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Bayesian look ahead one stage sampling allocations for selecting the largest normal mean

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Abstract

From two independent normal populations with unknown means and a common known variance, samples of unequal sizes are observed at stage 1. The goal is to find that population with the larger mean. Using the Bayes approach, optimum allocations ofm additional observations, at stage 2, are derived under the linear and the 0–1 loss.

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Authors and Affiliations

  1. Department of Statistics, Purdue University, 47907, West Lafayette, IN, U.S.A.

    S. S. Gupta

  2. Department of Mathematics, Statistics, and Computer Science (M/C 249), University of Illinois at Chicago, P.O. Box 4348, 60680, Chicago, IL, U.S.A.

    K. J. Miescke

Authors
  1. S. S. Gupta
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  2. K. J. Miescke
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Additional information

Research supported in part by NSF Grant DMS-8923071 at Purdue University.

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Gupta, S.S., Miescke, K.J. Bayesian look ahead one stage sampling allocations for selecting the largest normal mean. Statistical Papers 35, 169–177 (1994). https://doi.org/10.1007/BF02926410

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  • DOI: https://doi.org/10.1007/BF02926410

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