Admissible and minimax estimation of the parameter n in the binomial distribution
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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Detail(s)
Original language | English |
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Pages (from-to) | 451-466 |
Journal / Publication | Journal of Statistical Planning and Inference |
Volume | 113 |
Issue number | 2 |
Publication status | Published - 1 May 2003 |
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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.
Research Area(s)
- Admissibility, Binomial distribution, Minimaxity, Number of trials, Quadratic loss
Citation Format(s)
Admissible and minimax estimation of the parameter n in the binomial distribution. / Zou, Guohua; Wan, Alan T.K.
In: Journal of Statistical Planning and Inference, Vol. 113, No. 2, 01.05.2003, p. 451-466.
In: Journal of Statistical Planning and Inference, Vol. 113, No. 2, 01.05.2003, p. 451-466.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review