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An adaptive hierarchical Bayes quality measurement plan

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  • Partha Lahiri
  • Huilin Li

Abstract

The quality of a production process is often judged by a quality assurance audit, which is essentially a structured system of sampling inspection plan. The defects of sampled products are assessed and compared with a quality standard, which is determined from a tradeoff among manufacturing costs, operating costs and customer needs. In this paper, we propose a new hierarchical Bayes quality measurement plan that assumes an implicit prior for the hyperparameters. The resulting posterior means and variances are obtained adaptively using a parametric bootstrap method. Published in 2009 by John Wiley & Sons, Ltd.

Suggested Citation

  • Partha Lahiri & Huilin Li, 2009. "An adaptive hierarchical Bayes quality measurement plan," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(4), pages 468-477, July.
    • Handle: RePEc:wly:apsmbi:v:25:y:2009:i:4:p:468-477
    DOI: 10.1002/asmb.778
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    References listed on IDEAS

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    1. Roger J. Marshall, 1991. "Mapping Disease and Mortality Rates Using Empirical Bayes Estimators," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 40(2), pages 283-294, June.
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