期刊論文

學年 96
學期 1
出版(發表)日期 2007-08-15
作品名稱 A revisit to the common mean problem: Comparing the maximum likelihood estimator with the Graybill–Deal estimator
作品名稱(其他語言)
著者 Pal, Nabendu; Lin, Jyh-jiuan; Chang, Ching-hui; Somesh, Kumar
單位 淡江大學統計學系
出版者 Amsterdam: Elsevier BV
著錄名稱、卷期、頁數 Computational Statistics and Data Analysis 51(12), pp.5673-5681
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.
關鍵字 Admissibility; Inadmissibility; Asymptotic variance
語言 en
ISSN 0167-9473
期刊性質 國外
收錄於 SCI EI SSCI
產學合作
通訊作者
審稿制度
國別 NLD
公開徵稿
出版型式 紙本
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