淡江大學機構典藏:Item 987654321/20652
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    题名: A revisit to the common mean problem: Comparing the maximum likelihood estimator with the Graybill–Deal estimator
    作者: Pal, Nabendu;Lin, Jyh-jiuan;Chang, Ching-hui;Somesh, Kumar
    贡献者: 淡江大學統計學系
    关键词: Admissibility;Inadmissibility;Asymptotic variance
    日期: 2007-08-15
    上传时间: 2009-11-30 12:55:02 (UTC+8)
    出版者: Amsterdam: Elsevier BV
    摘要: For estimating the common mean of two normal populations with unknown and possibly unequal variances the well-known Graybill–Deal estimator (GDE) has been a motivating factor for research over the last five decades. Surprisingly the literature does not have much to show when it comes to the maximum likelihood estimator (MLE) and its properties compared to those of the GDE. The purpose of this note is to shed some light on the structure of the MLE, and compare it with the GDE. While studying the asymptotic variance of the GDE, we provide an upgraded set of bounds for its variance. A massive simulation study has been carried out with very high level of accuracy to compare the variances of the above two estimators results of which are quite interesting.
    關聯: Computational Statistics and Data Analysis 51(12), pp.5673-5681
    DOI: 10.1016/j.csda.2007.04.004
    显示于类别:[統計學系暨研究所] 期刊論文

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