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

✍ Scribed by Jean-François Angers; Duncan K. H. Fong

Publisher
John Wiley and Sons
Year
1994
Tongue
English
Weight
487 KB
Volume
41
Category
Article
ISSN
0894-069X

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✦ Synopsis

Let Yi -N(Bi, o?), i = 1, . . . , p, be independently distributed, where Bi and of are unknown. A Bayesian approach is used to estimate the first two moments of the minimum order statistic, W = min( Y I , . . . , Y,). 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.

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