A Quasi-Bayes sequential procedure for mixture

Ehud Makov, A. F.M. Smith

Research output: Contribution to journalArticlepeer-review

Abstract

Coherent Bayes sequential learning and classification procedures are often useless in practice because of ever-increasing computational requirements. On the other hand, computationally feasible procedures may not resemble the coherent solution, nor guarantee consistent learning and classification. In this paper, a particular form of classification problem is considered and a "quasi-Bayes" approximate solution requiring minimal computation is motivated and defined. Convergence properties are established and a numerical illustration provided.
Original languageEnglish
Pages (from-to)106-112
JournalJournal of the Royal Statistical Society. Series B: Statistical Methodology
Volume40
Issue number1
StatePublished - 1978
Externally publishedYes

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