Estimating moments of the minimum order statistic from normal populations—a bayesian approach

Jean‐François ‐F Angers, Duncan Fong

Research output: Contribution to journalArticle

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Abstract

Let Yi ∽ N(θi, σ i2), i = 1, …, p, be independently distributed, where θi and σ i2 are unknown. A Bayesian approach is used to estimate the first two moments of the minimum order statistic, W = min (Y1, …, Yp). In order to compute the Bayes estimates, one has to evaluate the predictive densities of the Yi's conditional on past data. Although the required predictive densities are complicated in form, an efficient algorithm to calculate them has been developed and given in the article. An application of the Bayesian method in a continuous‐review control model with multiple suppliers is discussed. © 1994 John Wiley & Sons, Inc.

Original languageEnglish (US)
Pages (from-to)1007-1017
Number of pages11
JournalNaval Research Logistics (NRL)
Volume41
Issue number7
DOIs
StatePublished - Jan 1 1994

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Ocean Engineering
  • Management Science and Operations Research

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