Advances in sequential bayesian work sampling

James R. Buck, Ronald G. Askin, Jose M.A. Tanchoco

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Sequential Bayesian work sampling has been previously shown to be both more efficient and more adaptable than traditional methods of work sampling. However, a few deficiencies of the Bayesian approach remained. The advances to that methodology shown here greatly reduce or eliminate those deficiencies. These advances include beta parameter maps, confidence subinterval estimation in closed form, preposterior analysis, estimation methods for remaining sample sizes, and other aids to the management of Bayesian work-sampling studies.

Original languageEnglish (US)
Pages (from-to)19-30
Number of pages12
JournalIIE Transactions (Institute of Industrial Engineers)
Issue number1
StatePublished - Mar 1983
Externally publishedYes

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering


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