Admissible and minimax estimation of the parameter n in the binomial distribution

Guohua Zou, Alan T.K. Wan

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    4 Citations (Scopus)

    Abstract

    In this paper, the problem of estimating the parameter n of the binomial distribution is considered under the assumption of both infinite and finite parameter spaces. A class of estimators, which include as a special case Sadooghi-Alvandi's [Ann. Statist. 14 (1986) 1634] estimator is considered; and the necessary and sufficient conditions for this class of estimators to be admissible are obtained, along with a new proof on the admissibility of Sadooghi-Alvandi's estimator. Furthermore, the minimax property of some estimators is investigated. © 2002 Elsevier Science B.V. All rights reserved.
    Original languageEnglish
    Pages (from-to)451-466
    JournalJournal of Statistical Planning and Inference
    Volume113
    Issue number2
    DOIs
    Publication statusPublished - 1 May 2003

    Research Keywords

    • Admissibility
    • Binomial distribution
    • Minimaxity
    • Number of trials
    • Quadratic loss

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