Short communication: A revisit to the common mean problem: Comparing the maximum likelihood estimator with the Graybill-Deal estimator

Authors:
Nabendu Pal;Jyh-Jiuan Lin;Ching-Hui Chang;Somesh Kumar
Affiliations:
Department of Mathematics, University of Louisiana at Lafayette, Lafayette, LA 70504, USA;Department of Statistics, Tamkang University, Tamsui, Taipei, Taiwan, ROC;Department of Applied Statistics and Information Science, Ming Chuan University, Taoyuan County, Taiwan, ROC;Department of Mathematics, Indian Institute of Technology, Kharagpur, West Bengal 721302, India
Venue:
Computational Statistics & Data Analysis
Year:
2007

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Abstract

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.