A revisit to the common mean problem: Comparing the maximum likelihood estimator with the Graybill–Deal estimator

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題名:	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
貢獻者:	淡江大學統計學系
關鍵詞:	Admissibility;Inadmissibility;Asymptotic variance
日期:	2007-08-15
上傳時間:	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
顯示於類別:	[統計學系暨研究所] 期刊論文

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